A Dozen Lessons from Murray Gell-Mann that Apply to Business, Investing and Life


Murray Gell-Mann is a theoretical physicist and was the winner of the Nobel Prize for Physics in 1969 for his work on the classification of subatomic particles. Gell-Mann is a Professor of Theoretical Physics, Emeritus at Caltech and a Distinguished Fellow at the Santa Fe Institute, which he co-founded in 1993. Caltech writes: “Gell-Man earned his PhD in physics at MIT and went on to study at Princeton under Oppenheimer, has devoted his scientific career to finding the ultimate elementary building block of matter, a search that has been compared to looking for the bottom of a well extending into infinity. The quest for the bottom of the well has led Gell-Mann through an Alice-in-Wonderland world of ‘strangeness’ and the ‘eightfold way’ to the wondrous ‘quark.’” A New York Times profile describes the range of his skills and interests: “He is a director of the John D. and Catherine T. MacArthur Foundation, member of the Council on Foreign Relations, adviser to the Pentagon on arms control, collector of prehistoric Southwest American pottery, amateur ornithologist, to name a few.” He is the author of the book The Quark and the Jaguar: Adventures in the Simple and the Complex.

  1. “Any entity in the world around us, such as an individual human being, owes its existence not only to the simple fundamental law of physics and the boundary condition on the early universe but also to the outcomes of an inconceivably long sequence of probabilistic events, each of which could have turned out differently.” “The fundamental law does not tell you exactly the history of the universe, but only gives probabilities for a gigantic number of alternative histories of the universe.” 

Perhaps the most important lesson I have learned from Gell-Mann is phrased perfectly by Howard Marks: “Many futures are possible, but only one future occurs.” In making that statement Marks gave a hat tip to Elroy Dimson who said: “Risk means more things can happen than will happen.,” but I imagine both he and Dimson have read Gell-Mann. Marks embellished on this idea further by saying “the future should be viewed not as a fixed outcome that’s destined to happen and capable of being predicted, but as a range of possibilities and, hopefully on the basis of insight into their respective likelihoods, as a probability distribution.” This idea that the future is should be viewed as a probability distribution was made even more valuable for me when I combined it with Charlie Munger’s ideas about the value of knowing what you do not know. These ideas were made even more valuable by the ideas of Richard Zeckhauser, which were best brought to life for me by a wonderful paper entitled: “Investing in the Unknown and Unknowable.” I could go on identifying other related ideas from other people, but I think you see my point. When you encounter a really big idea and it is reinforced by ideas from other great minds, it becomes even more powerful and useful. 

  1. “We live in a universe with an enormous amount of uncertainty. Quantum mechanical law can only give probabilities for alternative-different alternative histories of the universe. And all the things that are not predicted are nevertheless very important for determining the outcome. So that the particular events of the history of the universe are co-determined by the fundamental law and a whole series of intrinsically unpredictable accidents.” “Quantum mechanics gives us fundamental, unavoidable indeterminacy, so that alternative histories of the universe can be assigned probability.” “Sometimes the probabilities are very close to certainties, but they’re never really certainties.”

Gell-Mann’s point about inevitable uncertainty makes me think harder about the right way to make decisions in the presence of uncertainty. I like Zeckhauser’s definition of uncertainty, which makes clear that when potential states of the world are unknown, probability is not computable (ignorance) and that probability cannot be calculated if you do not know probably distribution (uncertainty).  Almost all of life is uncertain since the probability distribution impacting the future is rarely known with certainty.


Howard Marks talks about these ideas in the context of investing is his latest letter:

there are two things I would never say when referring to the market: “get out” and “it’s time.”  I’m not that smart, and I’m never that sure.  The media like to hear people say “get in” or “get out,” but most of the time the correct action is somewhere in between. Investing is not black or white, in or out, risky or safe.  The key word is “calibrate.”  The amount you have invested, your allocation of capital among the various possibilities, and the riskiness of the things you own all should be calibrated along a continuum that runs from aggressive to defensive.

In one of two posts I have written on Marks I quoted him as saying: “The future you get may be beneficial to your portfolio or harmful, and that may be attributable to your foresight, prudence or luck.  The performance of your portfolio under the one scenario that unfolds says nothing about how it would have fared under the many ‘alternative histories’ that were possible.” This point is fundamentally important since, as Michael Mauboussin points out, Investing is a probabilistic exercise. In any probabilistic field, you have to recognize that even great decisions won’t work out all of the time, and sometimes poor decisions will work out well.” Nobody can be right all the time, but a person can learn to be wrong less often and in that process gain an investing edge. In other words, we can learn to have a better investing process even though we can’t be right all of the time. The more humble you are about making predictions in environments involving uncertainty and the more you include a margin of safety in making these decisions, the better off you will be. I don’t think that the first word that comes to mind when anyone describes me would be humble, but I try to be very humble about what I can predict. Another point made by Zeckhauser that is important is his emphasis on portfolio optimization  as a skill needed by investors. The case of venture capital is an extreme example in the investing world, since “among the very top performing VCs, 4.5% of invested capital generates 60% of their funds’ returns.”


3. “In predicting things one always has only partial information.” “The existence of our galaxy, the development of our particular star, the sun, similarly depend on accidents, fluctuations that are intrinsically unpredictable. The emergence of the particular planets of our solar system, likewise. The details of the development of life on the Earth, likewise. The evolution of particular forms of life, likewise, depend on utterly unpredictable accidents.”

Gell-Mann’s ideas about unpredictable accidents are applicable in many contexts. For example, what Gell-Mann is talking about should make you more aware that if you are in favorable position in life a lot of that outcome is based on luck. People who ascribe moral superiority to themselves when outcomes are as based on luck as they are not being intellectually honest. Luck happens, both bad and good, and it has no moral dimension in terms of its outcome. The only moral aspect is related to the lucky giving back to the unlucky. As another example, Gell-Mann’s point reinforces the arguments Lean Startup advocates make about the value of conducting experiments using the scientific method in building a business or investing. If evolutionary outcomes depend on unpredictable accidents, then experimenting to test the evolutionary fitness of an idea is wise (another forms of portfolio optimization). The products and services created through this experimentation process that have greater fitness survive, and less-fit products and services die. Entrepreneurs have always experimented when creating or altering a business. What is different today is that modern tools and systems allow experiments to be conducted more cheaply and rapidly than ever before. Evolution has been put on steroids and is as a result faster and more powerful.   

  1. “Think how hard physics would be if particles could think.” “What I try to do in the book is to trace the chain of relationships running from elementary particles, fundamental building blocks of matter everywhere in the universe, such as quarks, all the way to complex entities, and in particular complex adaptive system like jaguars.”

Mauro Gallegati and Matteo Richiardi write: “complexity is ubiquitous in economic problems (although this is rarely acknowledged in economic modeling), since (i) the economy is inherently characterized by the interaction of individuals, and (ii) these individuals have cognitive abilities…’ Consider how hard it was for forecasters to predict the lath of a hurricane. A recent Bloomberg headline read: “A $150B misfire: How Disaster Modelers Got it SO Wrong.” Imagine how much harder that modeling would have been if particles could think and had emotions. The more macro the forecast, the more the effort is like trying to predict the actions of a hurricane composed of thinking and emotional particles. Howard Marks explains: “We don’t know what lies ahead in terms of the macro future. Few people if any know more than the consensus about what’s going to happen to the economy, interest rates and market aggregates. Thus, the investor’s time is better spent trying to gain a knowledge advantage regarding ‘the knowable’: industries, companies and securities. The more micro your focus, the great the likelihood you can learn things others don’t.”  Focusing on the simplest possible system (an individual company) is the greatest opportunity for an investor since a company is understandable in a way which may reveal a mis-priced bet. Howard Marks puts it simply:  “We don’t make macro bets.”

Eric Beinhocker explains how theories can go astray if it is assumed that people behave like particles (i.e., do not think or have emotions):     

My cartoonish summary would be that a group of very clever people in the late 19th century (Walras, Jevons, Menger, Pareto) wanted for very legitimate reasons to introduce mathematics and rigor into economics. But the tools they had at the time – primarily static equilibrium methods – were simply the wrong tools for the job. But they couldn’t have realized that at the time, and wrong tools were better than no tools, so their work set off a multi-decade creative burst of developing mathematical theories of the economy as an equilibrium system and shifting economics out of the philosophy department and into the new domain of social science. But as the neoclassical models became more elaborate they also became more detached from reality, and unfortunately the profession began to reward mathematical virtuosity more than empirical validity.

People in the real world are neither perfectly efficient nor fully rational because they think and have emotions. Markets do tend to discount information quickly, but they do not do so immediately and it rarely happens perfectly. Charlie Munger explains the implications: 

“I think it is roughly right that the market is efficient, which makes it very hard to beat merely by being an intelligent investor. But I don’t think it’s totally efficient at all. And the difference between being totally efficient and somewhat efficient leaves an enormous opportunity for people like us to get these unusual records. It’s efficient enough, so it’s hard to have a great investment record. But it’s by no means impossible. Nor is it something that only a very few people can do. The top three or four percent of the investment management world will do fine.”

5. Complex adaptive systems are systems that can evolve or learn or adapt, and they would include-such systems would include biological evolution as a whole, the evolution of biological organisms on the Earth, the evolution of ecological systems on the Earth. The telical evolution that preceded the first life. That’s called prebiotic chemical evolution, which one can try to imitate to some extent in the laboratory. And then, many things that arose as a result of biological evolution, for example, individual learning and thinking. Human cultural evolution, including such things as the evolution of language, the global economy as involving complex systems. All of these have a great many things in common, because learning, adaptation, and evolution are all very similar phenomena.  

I sometimes hear a person say that the study of complexity is not useful since it does not allow you to make specific predictions. The best answer to that argument is: how can knowing what you can’t predict not be valuable? For example, Charlie Munger wants to know where he will die so he can just not go there. This is just a part of Munger’s inversion approach to looking at the world and solving problems. The reason why so many great investors attend seminars and meetings at the Sante Fe Institute is that they want to know what they do not know and can’t predict. Charlie Munger believes:

“The way complex adaptive systems work and the way mental constructs work is that problems frequently get easier, I’d even say usually are easier to solve, if you turn them around in reverse. In other words, if you want to help India, the question you should ask is not “how can I help India,” it’s “what is doing the worst damage in India? What will automatically do the worst damage and how do I avoid it?” “Figure out what you don’t want and avoid it and you’ll get what you do want. How can you best get what you want? The answer: Deserve what you want! How can it be any other way?” 

  1. “There is simplicity and complexity in the universe. The picture that we have, at least. Simple underlying laws, but very complex results. And among these complex systems in the universe are systems like us, that can process information.” 

Michael Mauboussin describes the first of the three elements of “complexity” in this way: “the system consists of a number of heterogeneous agents, and each of those agents makes decisions about how to behave. The most important dimension here is that those decisions will evolve over time.” These heterogeneous agents might be ants, investors, businesses,  genes or neurons. Mauboussin makes a key point here for investors and business people about the significance of this element: “markets tend to be efficient when the agents operate in a truly heterogeneous fashion and the aggregation mechanism is working smoothly. Diversity is essential, both in nature and in markets, and the system has to be able to take advantage of that diversity.” When diversity breaks down, as was the case during the internet bubble or the lead up to the 2007 financial crisis, markets can get very inefficient. Collections of intelligent and diverse heterogeneous agents are capable of forming self-organizing, learning, adaptive collectives that can exhibit the “wisdom of crowds.”  The method that some people have pursued to study the interaction of heterogeneous agents is known as agent-based modeling.

  1. “You don’t need something more to get something more. That’s what emergence means. Life can emerge from physics and chemistry plus a lot of accidents. The human mind can arise from neurobiology and a lot of accidents, the way the chemical bond arises from physics and certain accidents. Doesn’t diminish the importance of these subjects to know they follow from more fundamental things plus accidents.” “The particular details of the history that we experience we can learn only by looking around us.”

Mauboussin: “The second characteristic of complexity is that the agents interact with one another. That interaction leads to the third—something that scientists call emergence: In a very real way, the whole becomes greater than the sum of the parts.” To say something is “complex” is not the same as saying something is “complicated.” Wendell Jones explains the difference: “Complicated linear and determined systems produce controllable and predictable outcomes. Complex adaptive systems can produce novel, creative, and emergent outcomes.” An investor like Howard Marks makes his work consistent with this idea by focusing on microeconomics economics rather than macroeconomics.  Microeconomics is orders of magnitude less complex and as a result is far less impacted by chaos and the flap of a butterfly’s wings. What you can do is focus on what you know best. We can know a fair amount about the present if we work and pay attention. We have zero information about the future.

8.“No gluing together of partial studies of a complex nonlinear system can give a good idea of the behavior of the whole.”

Mauboussin elaborates on the third element of complexity in this way: “The key issue is that you can’t really understand the whole system by simply looking at its individual parts. “You can’t make predictions in any but the broadest and vaguest terms.” Complex adaptive systems effectively obscure cause and effect.” “Complexity doesn’t lend itself to tidy mathematics in the way that some traditional, linear financial models do.” “Increasingly, professionals are forced to confront decisions related to complex systems, which are by their very nature nonlinear… ” A major implication of this point is that reductionist thinking and methods are not only useless but can lead to dangerous conclusions. It is not possible to make macro predictions by simply summing up micro empirical outcomes when complex systems are involved.

  1. “The word chaos is used in rather a vague sense by a lot of writers, but in physics it means a particular phenomenon, namely that in a nonlinear system the outcome is often indefinitely, arbitrarily sensitive to tiny changes in the initial condition.” 

An MIT summary of Stuart Kauffman’s book entitled At Home in the Universe reads as follows: “chaos theory, concerns the “butterfly effect” in which “a legendary butterfly flapping its wings in Rio changes the weather in Chicago.” This point highlights the sensitivity of complex systems to miniscule changes in initial conditions. Taken together, these considerations preclude the possibility of predicting long-term behavior of such systems.” How does this inform investment decisions? Chaotic systems are not always complex, and complex systems are not always chaotic. It depends.

“two states that are very close together initially and that operate under the same simple rules will nevertheless follow very different trajectories over time. This sensitivity makes it difficult to predict the evolution of a system, as this requires the initial state of the system to be described with perfect accuracy.”

10. “Complex adaptive systems have the wonderful property of exploring new possibilities and trying out new possibilities and spawning new complex adaptive systems, and so on.” 

I like to think about nests of complex adaptive systems. One complex system impacts others and spawns more complex systems and Evolution happens. Philip Nelson writes humorously: “At the dawn of the twentieth century, it was already clear that, chemically speaking, you and I are not much different from cans of soup. And yet we can do many complex and even fun things we do not usually see cans of soup doing.” Gell-Mann believes that this idea leads naturally to the conclusion that there are other forms of consciousness in the universe. Evolution on this planet reflects this same process. Ant colonies and immune systems are often used as an example to explain a complex how a system experiments and learns. Melanie Mitchell, the author of the book Complexity: A Guided Tour writes:

Both immune systems and ant colonies use randomness and probabilities in essential ways. The receptor shape of each individual lymphocyte has a randomly generated component, so as to allow coverage by the population of many possible pathogenic shapes. The spatial distribution of lymphocytes has a random component, due to the distribution of lymphocytes by the blood stream, so as to allow coverage of many possible spatial distributions of pathogens. The detailed thresholds for activation of lymphocytes, their actual division rates, and the mutations produced in the offspring all involve random or noisy aspects. Similarly, the movement of ant foragers has random components, and these foragers are attracted to pheromone trails in a probabilistic way. Ants also task-switch in a probabilistic manner. It appears that such intrinsic random and probabilistic elements are needed in order for a comparatively small population of simple components (ants or cells) to explore an enormously larger space of possibilities, particularly when the information to be gained is statistical in nature and there is little a priori knowledge about what will be encountered.  

  1. “Anyone having a creative idea even in everyday life has to shake up the usual patterns in some way to get out of the rut (or the basis of attraction)of conventional thinking, dispense with certain accepted but wrong notions and find a new and better way to formulate some problem.  [The stages of creativity are] actually very well-known:

a) Saturation-you fill yourself full of the contradiction between the problem you need to work on and the existing idea that’s somehow not good enough, or the existing method that is somehow not good enough to deal with the problem.

b) Incubation- After you’ve confronted this contradiction between what’s available and what’s needed, for a long time, apparently further conscious thought is no good anymore. And at that point, some sort of mental process out of awareness seems to take over, I guess what the shrinks would call the pre-conscious. It starts to cook this material.

c) Illumination- One day, while cooking or shaving or cycling, by a slip of the tongue or even while sleeping and dreaming, according to certain people, an idea suddenly comes.

d) Verification- And maybe the idea is right. See if it’s a good idea.”

Rob Goodman, who co-authored a book about Claude Shannon, made this comment about his creativity on Reddit:

I don’t mean to suggest that Shannon was lazy–like lots of remarkably successful people, he had his bouts of intense and concentrated activity. This was especially true in his younger years–we discuss some accounts from an acquaintance of his at the time he was working on his information theory paper, who says that Shannon would compulsively scribble ideas on napkins, or stare into space in deep concentration, or mention getting up in the middle of the night to work when struck by an idea. So when Shannon was in the midst of one of his highly creative periods, he certainly had a capacity for work to match anyone.

But what really distinguished Shannon was that he didn’t try to force it. We called our book A Mind at Play because we think that captures Shannon so well. He asked silly questions, loved tinkering in his workshop, and was often seen unicycling down the hallways of Bell Labs. He had a folder of “Letters I’ve Procrastinated on for Too Long.” And he approached his work in just the same spirit–we called it “play of the adult kind,” or play with ideas and concepts.

In other words, the main lesson we take from Shannon’s life in this regard is that the people who are most productive on the scale the matters–like, world-changingly productive–don’t worry about being productive every single hour. They can work intensely when they need to, but they also know how much is to be gained from letting the mind wander.

As an example, my friend Craig McCaw is like Shannon in the way he approaches life which enhances his creativity. I loved it when I got a message from him that he wanted me to fly with him in his vintage Beaver seaplane to have lunch somewhere in the middle of a business day. Flying or boating makes him happy and sparks his creativity. Some play combined with hard work makes him a more creative and therefore results in better business decisions. An entire company of people like Craig would not work well but a few people like him makes it stronger and more profitable.

12. “If someone says that he can think or talk about quantum physics without becoming dizzy, that shows only that he has not understood anything whatever about it.” 

When I first read the sentence in bold immediately above I remember thinking to myself: If quantum physics makes Gell-Mann dizzy, what hope do I have of understanding it? It also made me think about an essay written by Michael Citchton that is related to Gell-Mann:

Media carries with it a credibility that is totally undeserved. You have all experienced this, in what I call the Murray Gell-Mann Amnesia effect. (I call it by this name because I once discussed it with Murray Gell-Mann, and by dropping a famous name I imply greater importance to myself, and to the effect, than it would otherwise have.) Briefly stated, the Gell-Mann Amnesia effect works as follows. You open the newspaper to an article on some subject you know well. In Murray’s case, physics. In mine, show business. You read the article and see the journalist has absolutely no understanding of either the facts or the issues. Often, the article is so wrong it actually presents the story backward-reversing cause and effect. I call these the “wet streets cause rain” stories. Paper’s full of them. In any case, you read with exasperation or amusement the multiple errors in a story-and then turn the page to national or international affairs, and read with renewed interest as if the rest of the newspaper was somehow more accurate about far-off Palestine than it was about the story you just read. You turn the page, and forget what you know. That is the Gell-Mann Amnesia effect. I’d point out it does not operate in other arenas of life. In ordinary life, if somebody consistently exaggerates or lies to you, you soon discount everything they say. In court, there is the legal doctrine of falsus in uno, falsus in omnibus, which means untruthful in one part, untruthful in all. But when it comes to the media, we believe against evidence that it is probably worth our time to read other parts of the paper. When, in fact, it almost certainly isn’t. The only possible explanation for our behavior is amnesia.

Imagine what Gell-Man must think when reading someone else’s article on quantum mechanics. I am reminded of the scene from the 1977 movie Annie Hall when the character played by Woody Allen is able to make the media philosopher Marshall McLuhan appear to correct the view of someone who is pontificating in the movie line. McLuhan tells the man: “I heard what you were saying. You know nothing of my work.”

Gell-Mann is often not satisfied even by the way he writes about his ideas. His perfectionism is legendary, illustrated by his struggles to write his book The Quark and the Jaguar, as described in the New York Times:

Uneasy with any work that isn’t world-class perfect, Gell-Mann for years found writing excruciating, and the book was no exception. His agent thought a ghost writer would help. Gell-Mann plowed through three. One, who had helped produce the 32-page proposal that sold the book, bowed out after that point and wrote his own book; the next one simply couldn’t bear the flaws Gell-Mann would find in everything he wrote and dropped out; a third wisely decided his three-month job was only to edit and encourage as Gell-Mann agonized over his own hen-scratchings. The chapters Gell-Mann finally delivered were written by no one but himself. By then, having fallen far behind schedule, Gell-Mann was dropped by his first publisher; he found a second one, but nearly exhausted its patience with his last-minute corrections.

P.s., Here is an interesting paper from 2016 that many readers may not be aware of that Gell-Mann co-wrote entitled: “Exploring Gambles Reveals Foundational Difficulty Behind Economic Theory (and a Solution!).” In a press release announcing the paper Gell-Mann is quoted as follows:

…the following perspective arose: to assess some uncertain venture, ask yourself how it will affect you in one world only — namely the one in which you live — across time,” Gell-Mann continued. “The first perspective — considering all parallel worlds — is the one adopted by mainstream economics,” explained Gell-Mann. “The second perspective — what happens in our world across time — is the one we explore and that hasn’t been fully appreciated in economics so far.” https://publishing.aip.org/publishing/journal-highlights/exploring-gambles-reveals-foundational-difficulty-behind-economic




















A Dozen Lessons about Business and Life from Jimmy Iovine


Jimmy Iovine started his career as a sound engineer. He used that experience to become a record producer and later translated that set of skills to becoming a co-founder of Interscope Records. In 2006, Iovine and Dr. Dre founded Beats Electronics, which they later sold to Apple for $3 billion. As an aside, I would have liked to have written about Dr. Dre too in his post, but he is a man of few words.

  1. “I don’t have a rear view mirror.” “I never celebrated a success. There are no victory laps. I’m always moving forward.” “The most important thing I ever learned: No matter how ugly it gets, keep moving.” “Going backwards is not an option.”

Allen Hughes, who directed the documentary The Defiant Ones has said that the mentality reflected in the six bolded sentences above is:

The thing that they both have in common is that they literally don’t look back at anything they’ve accomplished. They don’t talk about it. They’re not nostalgic at all about any accomplishments or things they’ve been through. They just keep moving. They don’t have a rear view mirror.

As an example of putting this idea into practice, Iovine has said that he hid his first gold record in his basement because it was about past achievements, not future goals. The two partners are all about the work they are doing right now. They refuse to get sentimental or boastful and instead devote themselves to the present and how that will impact the future. Hughes has also said about Iovine and Dre:

What they both taught me the most and what they most have in common is when they get focused on something—creatively or passionate about anything in their life—that’s all they talk about and that’s all they live, breathe and eat. They don’t let any other noise come into their vision they just have blinders on. They don’t have extra conversations about sports or politics, they’re just so focused on what they’re doing. I took many, many life lessons from this but while I’m very passionate, they really taught me how to focus or tune out noise that doesn’t have anything to do with what you’re doing. As we get older that becomes more precious—to tune out the bullshit.

  1. “My proudest thing in my career is that I was able to change it three times. And I’m happy about that, I couldn’t have done the same thing my whole life, I would’ve gone nuts. I couldn’t do it because I do things based on impulsive excitement and I’m just not that guy that can do something for 50 years and be excited about the same thing. I can’t do it.”

Iovine’s experience in making these three career changes illustrates that this process can be positive, especially if you are willing to work hard and can hustle. Not only is a career change possible but it is likely to be essential given how fast the economy and world are changing. People will, for better or worse, increasingly need to repot themselves as they would a houseplant. That will necessarily take some bravery.  But since we all get root bound at some point in our careers and the change can potentially be a positive experience. One attribute that can help people navigate a change like this is to remain opportunistic. Occasionally an opportunity will come along that has a big upside and a small downside and you will need to be ready to take advantage of that. To illustrate that point, author and filmmaker Nelson George has said that Iovine “is one of the few — and it’s a very small group — who were part of the height of rock in the ’70s and ’80s with some of the greatest musicians of the era, who was able to see the value in hip-hop and make the move into hip-hop pretty seamlessly.”

On a personal note, one career change I made happened in 2002 after the Internet and telecom bubbles popped (there were two separate but related bubbles). The wireless and telecom industries were getting boring. Even on the financial side, the big opportunities were gone. The suits were taking over. Pirates were being asked to join the navy. Consolidation had already happened and would continue to happen. My investing thesis at the time was all about software anyway and so I decided that this would be the basis of my new career. I did not “go back to school” in 2002 but rather redoubled my efforts to become more knowledgeable about software. I read even more voraciously than usual about software and actively sought out the best teachers and experts. Mark Cuban said once that after you graduate from college one very valuable trick is to find jobs that pay you to learn. Cuban’s point is a very important idea regardless of whether your education stops at high school or extends to graduate school.

  1. “Just because you did something once doesn’t mean anything. You have to be willing in your heart to begin again every day. The minute I’m not willing to do that, I will retire. When we did Beats, we had to begin again. Nobody at Best Buy knew who we were. Did they care we had produced a record? They didn’t give a shit.” “Don’t believe your own bullshit. If I were going to teach a course, it would be called ‘Don’t Breathe Your Own Exhaust.’”

The business world is filled with people who have created a single successful business. That can be very impressive on one end of the spectrum or at the other end of the spectrum more luck than anything else. What exactly is luck and what is skill is an interesting topic and, as always, the writing of Michael Mauboussin is the “go to” source  trying to figure out what is skill and what is luck. Luck comes in a lot of different forms in the business world. For example, some people are suited from birth to do what they do while others never get the chance to do what they would be best suited for. Other people would have been a success no matter what they decided to do as a result of winning the genetic lottery. Business people who particularly impress me are those that have created something valuable multiple times. Iovine has obviously been successful in multiple business settings. As another example of this from my personal life, I worked with Craig McCaw for many years. McCaw created a huge cable television business from virtually nothing and after that McCaw Cellular Communications. After selling both businesses McCaw resurrected Nextel. As another example, Steve Jobs was fabulously successful at creating different business. Bill Gates has done the same thing and is now changing the world with his philanthropy.

  1. “I’m interested in listening to the people who walk in the door. If your ego and your accomplishments stop you from listening, then they’ve taught you nothing. There are geniuses, savants; I’m not one of them. I work hard.” “A diploma is really just your learner’s permit for the rest of the drive through life. Remember, you don’t have to be smarter than the next person, all you have to do is be willing to work harder than the next person.”

I have been lucky enough to be able to watch and assist some of the great entrepreneurs and investors work at very close range during my working like. This is has been a boon for my career since being able to observe very smart, creative and motivated people work is like going to school (if you are paying attention). In particular, building or fixing a business, whether inside a big company or in a startup, is a wonderful environment since there is so much learning going on. I do have one very unusual friend who almost never reads which astounds me since I read so much. He is nevertheless fabulously successful since he is nearly always around many smart people in cutting edge situations. He learns by taking to smart people. I don’t know anyone else like him, but he is an interesting case.

  1. “I learned my work ethic from Springsteen. I was a guy who would say, ‘Five o’clock, I’m out of here.’ Springsteen worked all the time. We were in a room with no window—no one ever knew what time it was.”

There is rarely a substitute for hard work. All of the great entrepreneurs I have known work very hard. One great example of the value of hard work is Bill Gates who said once on a Reddit: “20 years ago I would stay in the office for days at a time and not think twice about it. I had energy and naiveté on my side.” He made a similar point in a BBC interview “I knew everyone’s license plates so I could look out in the parking lot and see, when did people come in, when were they leaving. Eventually I had to loosen up, as the company got to a reasonable size.”

One slight variation on what I just said about hard work are a small number of founders and managers who sometimes seek out talented but “relatively lazy people” as employees since, as one of my friends likes to say, “they tend to find simpler and less costly ways to do things.” His belief is that these “relatively lazy people” will find short cuts that create a competitive advantage for a business. I should emphasize that this exception does not apply to people who are too lazy to work but rather to people who seek simpler methods that do not compromise quality. That preference for a small number of talented relatively lazy people who still seek high quality outcomes is a very narrow exception, but it is an interesting twist.

  1. “You have talent, you give them the keys and let them drive.” “What happened was, those first four years [working with Springsteen, Smith and John Lennon], I realized where the magic comes from, and it’s not from me.” “I always knew which side of the glass was more important.” “I’m not a humble guy. I just don’t believe my own bullshit.”

Iovine is saying that you should let “the talent” do their job. Iovine’s point is reflected in an old saying that you are not going to detect burglars better than your dog. This is an old idea that may of first been written down by Brian Melbancke in his novel from 1583 entitled Philotimus. In that novel Melbancke wrote: “It is smal reason you should kepe a dog, and barke your selfe.” Iovine is not saying that you should relinquish control of everything. Jim Barksdale likes to say: Now I’m the President around here. So if I say a chicken can pull a tractor trailer, your job is to hitch ’em up.” “If we have data, let’s look at data. If all we have are opinions, let’s go with mine.” But if the question involves the software that is used in an Internet browser a smart manager like Barksdale is going to defer to someone like Marc Andreessen.

  1. “Get in the room with the best people you can and open your heart, ears, and mind. Open up and learn. Be of service. Because if you’re of service, they will teach you. With Lennon and Springsteen and Smith, I knew that I had to be of service.” “John Lennon, Bruce Springsteen, and Patti Smith — were my college education.”

Yogi Berra famously said: “You can observe a lot by just watching.” When you get an opportunity like I have had in my business life to work closely with great managers and founders, what you learn is invaluable. One key thing you learn is that there are many ways to be successful. As an example, Craig McCaw and Bill Gates are very different people with very different styles. Bill Gates is more digital in his approach and Craig McCaw is more analog. They both surround themselves with diverse teams who make them better. One related point is that you should work actively put yourself in situations where you can learn from smart people.

  1. “Some of the best advice I’ve ever gotten [was] to look at the bigger picture.” “The thing about seeing the big picture and being self-aware is knowing that it’s not about you. It’s about the big picture. It’s not about you. It’s not. This is not about you.”

Good things happen when you help other people. Some people might say “that is karma,” but I am more practical and instead believe it is Professor Cialdini’s principle of reciprocity at work. Caldini writes: “A Hare Krishna devotee presses a flower or a copy of the Bhagavad-gītā into your hand (that happened to me), or a store gives you free samples, and you feel awkward about taking it for free. You end up giving money or buying something you don’t want.” This reciprocity idea as described by Iovine reminds me of an experiment conducted by a a sociologist at Brigham Young University who decided to see what would happen if he sent Christmas cards to total strangers.

He went out and collected directories for some nearby towns and picked out around 600 names. “I started out at a random number and then skipped so many and got to the next one,” he says. To these 600 strangers, Kunz sent his Christmas greetings: handwritten notes or a card with a photo of him and his family. And then Kunz waited to see what would happen. But about five days later, responses started filtering back — slowly at first and then more, until eventually they were coming 12, 15 at a time. Eventually Kunz got more than 200 replies. “I was really surprised by how many responses there were,” he says. “And I was surprised by the number of letters that were written, some of them three, four pages long.”

When you give to others in an intelligent way by being of service to them you inevitably get good things in return.

  1. “The real thing is that we are all frightened. If you are not frightened you are not original. Everyone’s frightened. It’s how you deal with that fear. It’s very very powerful. And what you’ve got to do is get it as a tailwind instead of a headwind. And that’s a little bit of a judo trick in your mind. And once you learn that, fear starts to excite you. Because you know that you are going to enter into something and try it and risk. And once you can get going, it’s a very powerful thing.”

Writing something like this blog post or a book should create a little bit of fear or it is not likely it will be original or valuable. For better or worse, the tools created based on today’s internet will inevitably expose your work product to attacks. Fear is an odd motivator. To little is bad and to much can be debilitating. The good news is that as you get older you cease giving a damn what people think. If you get immobilized by fear you are wasting a great opportunity. Take a risk. Every time I push publish on my blog, send in a book manuscript or send a Tweet I am taking a risk. If I am not creating some friction in doing so, I will very likely not achieve anything positive.

  1. “I live on the edge of this table, and if I get too comfortable on its surface, I lose what it is I’m trying to do. It’s all about balancing risk with overindulging on comfort.”

There was an article in the New York Times recently that talked about the power of getting outside of your comfort zone.  The author wrote:

The times in my life during which I’ve felt happiest and most alive are also the times that I’ve been the most unbalanced. Falling in love. Writing a book. Trekking in the Himalayas. Training to set a personal record in a triathlon. During these bouts of full-on living I was completely consumed by my activity. Trying to be balanced — devoting equal proportions of time and energy to other areas of my life — would have detracted from the formative experiences. It’s not just me. Nearly all of the great performers I’ve gotten to know — from athletes to artists to computer programmers to entrepreneurs — report a direct line between being happy, fulfilled and at their best and going all-in on something.

If you find something you are passionate about not only does life get better but you do better work. Consider yourself blessed if you get to tap dance to work like Warren Buffett. Even if you only sort of tap dance to work that is better than a poke in the eye with a sharp stick.

  1. “The first project I produced: Foghat. I did it for the money. At the time, you get paid three points to be a producer, and their last album sold 4 million. So I immediately said, ’20 cents a record… that’s $800,000!’ I’m getting $10 an hour as an engineer. I’m like, ‘I’m in.'” “I brought my girlfriend to the sessions. I let her run the tape machine.”

Iovine was famously fired by Foghat for the reasons Iovine identifies in the above quotes. That was not a good thing for Iovine at the time, but it was a good thing that he learned from the experience. A wise goal at any time in life is to make some new mistakes since otherwise you are not learning and growing as a person. Fortunately Patti Smith and other musicians believed in Iovine despite his mistakes with Foghat and he had another opportunity to prove that he was a talented and productive team member.  Take some risks. Learn some things. Make things happen. Don’t be afraid to fail sometimes. Be a bit of a rebel. Your life will be better and you will be happier if you do. Not giving a damn about what other people think when you are trying to be creative can be a superpower if you do this judiciously when the time is right if he potential upside is enormous and the downside is limited. Beat was a $3 billion exit and what they had to loose was what they invested.

  1. “Musicians believe right now that there’s very little money in the recorded music business. So a lot of them are aiming their goal to be nothing but promotion.” “Not every industry was meant to last forever. The record industry needs to do something that artists can’t do for themselves. Or else there’s no reason for it to exist.”

I have written several blog posts on the problems and opportunities that exist in the entertainment industry. I will link to them immediately below instead of repeating the points I made in those posts. One argument I have heard that is not in those posts: a major purpose of the record labels is to act as a bank since the musicians will invariably blow through all the money they have and will need an advance of funds to finance their next creative period. I have a friend who knows the music business very well who said to me several times his business is a place where you can take money in but you rarely get to take it out. What he was saying is people who make a fortune in some other business sometimes decide to take a significant amount of their cash and try to put it to work in the music business. These newbies have a lot of fun hanging out with famous musicians at parties, but the financial result is rarely pretty since they are outside of their circle of competence.

A Dozen Things You can Learn from Biggie Smalls (The Notorious B.I.G.) About Business  https://25iq.com/2016/11/11/a-dozen-things-you-can-learn-from-biggie-smalls-the-notorious-b-i-g-about-business/

A Dozen Things I have Learned About Business from Rza (the founder of Wu-Tang Clan) https://25iq.com/2016/01/02/a-dozen-things-i-have-learned-about-business-from-rza-the-founder-of-wu-tang-clan/

A Dozen Things I’ve Learned About the Music Business (and Businesses Like It) https://25iq.com/2016/09/03/a-dozen-things-ive-learned-about-the-music-business-and-businesses-like-it/

A Dozen Things I’ve Learned from Louis C.K. about Money, Investing and Business https://25iq.com/2016/05/28/a-dozen-things-ive-learned-from-louis-c-k-about-money-investing-and-business/

A Dozen Things I’ve Learned From Comedians About the Business of Life  https://25iq.com/2014/12/19/a-dozen-things-ive-learned-from-comedians-about-the-business-of-life/



















A Dozen Lessons about Investing and Money from Dan Ariely

Dan  is a Professor of Psychology and Behavioral Economics at Duke University and the founder of the Center for Advanced Hindsight. His research and work is about  how people actually act in the marketplace, as opposed to how they should or would perform if they were completely rational. His books include Predictably Irrational, The Upside of Irrationality, The Honest Truth about Dishonesty, and Payoff. His next book is entitled: Dollars and Sense: How We Misthink Money and How to Spend Smarter and will arrive in stores in November.

  1. “We’re such good storytellers that we come up with stories that portray us in good ways, so we don’t always even see our own mistakes. And then on top of that, it’s about our social standing, and admitting failure also admits that we might be wrong in the future.” “We all want explanations for why we behave as we do and for the ways the world around us functions. Even when our feeble explanations have little to do with reality. We’re storytelling creatures by nature, and we tell ourselves story after story until we come up with an explanation that we like and that sounds reasonable enough to believe. And when the story portrays us in a more glowing and positive light, so much the better.” 

A New York Times reviewer of Airely’s book Predictably Irrational describes one of his foundational conclusions as follows: “We aren’t cool calculators of self-interest who sometimes go crazy; we’re crazies who are, under special circumstances, sometimes rational.” The situations in which human are not rational are sufficiently predictable that systems can be created to achieve Airely’s goal of: “gaining a better understanding of our ability to make decisions, and identifying the places where we fall short, in order to better design products, interventions and policies.” In short, by understanding biases that can impact human behavior we can become better choice “architects.” For example, by creating the right structure we can make decisions more or less likely to happen depending on the results we want to achieve. Here is a grim but powerful example of how making something harder changes behavior:   

Prior to the 1950s, domestic gas in the United Kingdom was derived from coal and contained about 10-20% carbon monoxide (CO). Poisoning by gas inhalation was the leading means of suicide in the UK. In 1958, natural gas, virtually free of carbon monoxide, was introduced into the UK. By 1971, 69% of gas used was natural gas.  Over time, as the carbon monoxide in gas decreased, suicides also decreased. Suicides by carbon monoxide decreased  dramatically, while suicides by other methods increased a small amount, resulting in a net decrease in overall suicides, particularly among females.

If this change can reduce the level of suicide imagine how much it can increase the willingness of people to sign up for a savings programs or a 401(k). Decision-making frictions can have positive or negative impact depending on the desired outcome. people can be nudged just like frames.


  1. We look at the most recent evidence, take it too seriously, and expect that things will continue in that way.” “If you think about the creation of asset bubbles, that’s always what happens. Things go up and up and up, and we start thinking it has to always go up.” “It’s very hard for us to deal with lots and lots of information. Of course, today we’re getting lots and lots of information, so what do we do when we get too much information? We simplify. We use heuristics. We rely on only part of the information. On the most salient information. And that, of course, means that the most salient information is probably the information everybody else knows, as well; so we become less independent in our opinions from other investors. If everybody is in information overload, and we all do simplifications, then what happens is that we follow the simplest source of information, which is probably common to everybody.” Recency bias and herding. 

A human brain has many taxing decisions to make all day long. It naturally look for shortcuts and was to reduce cognitive load. It has a preference for readily accessible information like recent memory, over the hard work of thinking and analysis. If you have seen something recently is is easier to remember and take into account. People who have seen a stock or a market index go up recently are more likely o think it will go up more. People who have seen a picture of some who has won the lottery and more likely to believe that they will win the lottery. Nothing sells more lottery tickets than pictures in the news showing ordinary person holding a cardboard check from the lottery board. The tendency of people to follow the crowd is illustrated by a story that Warren Buffett likes to tell about a deceased oil prospector who is told by St Peter that Heaven’s allocation for his profession is full. The speculator yells “Oil discovered in Hell.” A stampede of people streams out of Heaven toward Hell. St Peter informs the prospector that he is welcome pass through and enter heaven. “No thanks,” said the prospector. “I’m going to check out that oil discovered in Hell rumor. Maybe there is some truth in it after all.” 

  1. “Money is really about opportunity cost.  Every time you buy coffee, the money comes from something else. What is this something else? We don’t envision it. With money, the trade offs are really unclear.” “Every time we buy something, it’s about what we are not going to be able to do in the future.” “The problem with opportunity cost is that opportunity cost is divided among many, many things.” Opportunity cost.

Charlie Munger is a strong believer in making decisions based on opportunity cost.

“In the real world, you uncover an opportunity, and then you compare other opportunities with that. And you only invest in the most attractive opportunities. That’s your opportunity cost.” “We’re guessing at our future opportunity cost. Warren is guessing that he’ll have the opportunity to put capital out at high rates of return, so he’s not willing to put it out at less than 10% now. But if we knew interest rates would stay at 1%, we’d change. Our hurdles reflect our estimate of future opportunity costs.” “Warren is scanning the world trying to get his opportunity cost as high as he can so that his individual decisions are better.”

When some asked you to buy something your decisions should not be limited to that question. The better question to ask is: Of all of the things I can buy or otherwise do with this money, is this what I want to do?  The question should not be: should I buy stock X. Instead, out of all the stocks or other investments in the world other should I buy X?

  1. “When things like complex financial instruments are difficult to evaluate, it’s easier for us to rationalize unethical behavior and the effects of conflicts of interest become larger. Finally, when other people around us behave similarly, conflicts of interest rule even more.” “The overall market for annuities is bad because it is very obscure. It is hard to price. And annuity companies can use lots of hidden fees and costs. If you think about it, it’s a market where most people who sell annuities get their commissions upfront which tells you that it’s probably (a) a hard thing to sell, but (b) that the companies need to incentivize sales people to sell them, which I think suggests (c) that there has to be something quirky about the whole system.” Incentive caused bias.

Charlie Munger says: “Where you have complexity, by nature you can have fraud and mistakes. You’ll have more of that than in a company that shovels sand from a river and sells it.” As an example, Munger says the U.S. healthcare system is “ridiculous” in its complexity. “The whole system is cockamamie,” he has said. There is he value in keeping an investment plan and investment decisions simple. You will make fewer mistakes and be a happier person. Research Affiliates makes three key points about this bias:

  • A preference for complexity is almost hardwired into investors, their agents, and asset managers because the intuition is that a complicated investment landscape requires a complex solution; a complex strategy also supports a higher fee from both agents and managers.
  • Research shows that simple, low-turnover and complex, high-turnover strategies perform similarly on a before-fee basis, suggesting the former may have the advantage after tax.
  • Simplicity leads to better investor outcomes not because simplicity in and of itself produces better investment returns, but because a simple strategy encourages investors to own their decisions and to less frequently overreact to short-term noise.

Munger makes the point with a fishing story: “I think the reason why we got into such idiocy in investment management is best illustrated by a story that I tell about the guy who sold fishing tackle. I asked him, ‘My God, they’re purple and green. Do fish really take these lures?’ And he said, “Mister, I don’t sell to fish.’”

  1. “A man’s satisfaction with his salary depends on (are you ready for this?) whether he makes more than his wife’s sister’s husband. Why the wife’s sister’s husband? Because (and I have a feeling that Mencken’s wife kept him fully informed of her sister’s husband’s salary) this is a comparison that is salient and readily available.” Availability bias

An idea or a fact should not be taken more into consideration I making a decision merely because it is easily available to you. Shark attack or a plane crash is not more likely because it is vivid. You are not more likely to win the lotto because you saw a winner on TV. A story bout X that you have read recently will tend to impact your decisions more than one you read years ago. Overcoming a dysfunctional heuristic like availability bias is a trained response.

  1. “Why does cash feel so different? The agony of parting with our money has to do with the saliency of, do we see this money going away? And it has to do with the timing of whether the money is going away at the same time we’re consuming.” “For example, we find that if you have a coin flip that you have a 50% chance of making $1,100 and a 50% chance of losing $1,000. The expected value is positive, but we don’t think of it as positive. We think, “Oh, my goodness. If I lost $1,000, I would be very miserable. If I won $1,100 I would be happy, but it wouldn’t offset it, so let me not take that bet.” Now, we think that the reason is evolutionary. If you think about nature, if you get something good (like you get to eat more food and so on) that’s a good thing, but if you do something bad, you can die. So nature has kind of tuned us to look at the negative side because if you get a bit more food, a bit more money or whatever, there’s a positive expected value but it’s limited. Whereas on the negative side, you can lose a lot. So because of that we just attune more to losses.” Loss aversion.

Michael Mauboussin writes: “One of prospect theory’s most important contributions to finance is loss aversion, the idea that for most people, losses loom larger than corresponding gains.  The empirical evidence suggests we feel losses about two to two-and-a-half times more than we feel gains. Loss aversion is a clear-cut deviation from expected utility theory.” Charlie Munger puts it this way: “People are really crazy about minor decrements down. Huge insanities can come from just subconsciously over-weighing the importance of what you’re losing or almost getting and not getting.”

7.”There are wealthy gentlemen in England who drive four-horse passenger coaches 20 or 30 miles in the summer because the privilege costs them considerable money, but if they were offered wages for the service, that would turn it into work, and then they would resign.” [Quoting Mark Twain] Anchoring

Anchoring is a tendency of people to grab on to inputs just because they are available. James Montier describes the bias as follows:  “In the absence of any solid information, past prices are likely to act as anchors for today’s prices.   For example, financial analysts often fail to revise their estimates since they get anchored to prior numbers. (they revise too late to be useful). Experiments have shown that if you ask a professional to work in behalf of the poor for free you get a much better response than if you ask them to work at a reduced rate. Free work on behalf of the less fortunate activates their desire to contribute to a community. Partial payments tend to activate anchoring which make them unhappy since they feel they have incurred a loss.

8. “People are always willing to take money from their future self, but then that puts the future in danger. So we have to work on getting people to think about how much they are really spending and also how they can invest in the future. That will take more of an effort as technology makes spending money easier to do.” “If you think about an environment in which we have to think long-term and abstractly, that’s just not something we’re good at.  Saving is about now versus later, it’s about concrete versus abstract, and we don’t do those well.” Present biased preference.

A time preference can be quantified as the amount of money required to compensate the consumer for foregoing current consumption. For example,

9. “Retirement is especially difficult because we not only don’t know exactly what we’re giving up, it’s also far away in the future.  That makes it very, very difficult to think about.  It’s called hyperbolic discounting — we just care less dramatically about the future so not only is it hard for us to understand what we are giving up, it’s also really, really delayed.” “If you think about the opportunity cost of money — if I spend a thousand dollars now on a new bicycle I know what I’m getting.  If I put it into my retirement account I don’t really know what I’ll get in the future.” Hyperbolic discounting.

Companies like Starbucks know that people will pay several dollars for a coffee house experience even though on an annualized basis it eats up a big share of their after-tax income. People like benefits that are available NOW—which is why they tend to not save for retirement and eat too many calories. The investor too often says: “To heck with the 401(k), let’s buy a waterski boat with a disco ball.”

10. “If it’s more difficult to get credit, it might make people feel more pain of paying and therefore spend less.” “I think one of the bigger problems today is how easy it is to spend money. I see a lot of younger people who get way out of whack with the reality of money because tech enables it. You order food from your phone because it is easy and someone else is doing the work of making it, but that also adds up over time. That may not be great for your finances long term because you stop thinking about how much money you’re spending each day. That feeds into all sorts of investment decisions over time.” Loss Aversion.

In my blog post on Richard Thaler I wrote:

“Hundreds of studies confirm that human forecasts are flawed and biased. Human decision making is not so great either. Again to take just one example, consider what is called the ‘status quo bias,’ a fancy name for inertia. For a host of reasons, which we shall explore, people have a strong tendency to go along with the status quo or default option.” Sales and marketing departments love status quo bias. For example, magazines often offer free trials or issues at a reduced price if the customer agrees that the business can continue to send them issues until they actively end the subscription. When making decisions people tend to follow the adage: “when in doubt, do nothing.” For this reason, getting a customer’s credit card information is a holy grail for marketers, who hate it when credit cards expire. Customers know this to some degree, which means they are reticent to hand out their credit card data even for a free trial. The incentives must be significant to obtain customer credit card data as a result.

  1. “Buffett gave unsigned checks for $10,000 to his children, promising to sign them if he was over target weight by a certain date. Many people use commitment devices to try to keep their weight down, but Buffett’s idea had a big flaw: his children, spotting a rare opportunity to get money from the notoriously frugal billionaire, resorted to sabotage. Doughnuts, pizza, and fried food mysteriously appeared whenever Buffett was home. In the end the incentives worked: even with his children’s sabotage, the Oracle kept his weight down, and his checks went unsigned. But had he been purely rational, no commitment device would have been needed.” Nudging.

It is possible to use a bias that is dysfunctional for positive purposes as Buffett has done here. Most certainly. Charlie Munger has said:  “The system of Alcoholics Anonymous: a 50% no-drinking rate outcome when everything else fails? It’s a very clever system that uses four or five psychological systems at once toward, I might say, a very good end.”  Richard Thaler tells this story to talk about why people need help:

I was having a dinner party for fellow economics grad students. Before dinner I served some cashew nuts along with cocktails, and everyone kept eating them. Soon their appetites were in danger, not to mention their waistlines. I grabbed the bowl and hid it in the kitchen. People were (a) happy, and (b) they realized their reaction conflicted with traditional economic theory. Econs are better off with more choices. We humans actually need help controlling our impulses—nudges.

  1. “Our irrational behaviors are neither random nor senseless- they are systematic and predictable. We all make the same types of mistakes over and over.” “One of the most underused interfaces in human decision-making is the calendar. If you think about it, the calendar does many, many things wrong. But one of the interesting things about the calendar is that when you have something there that is set there’s a good chance that you will actually go ahead and do it.”  “I want to know if we can start building ways of preventing risks. Can reminders really help people? We all know that you get a lower price on auto insurance if insurers think you are less likely to speed. What if we started sending reminders to people about speed or remind them of some of the long-term consequences that could result from speeding?”

Another example of a dysfunctional bias involves what a  New York Tines reviewer of Predictably Irrational pointed out that: “People aren’t just loss-averse; they are also effort-averse.” They also have status quo bias. Some countries have an opt-in system for organ donation. The direction they give is: “Please check this box if you would like to participate in the organ donation program.” Other countries have an opt-out system. This result of this choice architecture is striking.


That brings this post bask to the first point above. Airley says that if you ask people why they made their organ donation choice the inevitably come up with a story that somehow justifies their decision regardless of whether it is yes or no.


Not released yet:– Dollars and Sense: How We Misthink Money and How to Spend Smarter November 7, 2017 https://www.amazon.com/Dollars-Sense-Misthink-Money-Smarter/dp/006265120X/ref=sr_1_7?ie=UTF8&qid=1503168432&sr=8-7&keywords=dan+ariely

Dan_Ariely, The Honest Truth About Dishonesty: How We Lie to Everyone–Especially Ourselves

Dan_Ariely, Payoff: The Hidden Logic That Shapes Our Motivations https://www.amazon.com/Payoff-Hidden-Logic-Shapes-Motivations/dp/1501120042/ref=sr_1_3?ie=UTF8&qid=1503168432&sr=8-3&keywords=dan+ariely











Buffett and his attempts at self-control





A Dozen Attributes of a Scalable Business

“A startup is a company designed to grow fast. Being newly founded does not in itself make a company a startup. Nor is it necessary for a startup to work on technology, or take venture funding, or have some sort of ‘exit.’ The only essential thing is growth. Everything else we associate with startups follows from growth. To grow rapidly, you need to make something you can sell to a big market. That’s the difference between Google and a barbershop. A barbershop doesn’t scale.”  Paul Graham

“A startup is a temporary organization designed to search for a repeatable and scalable business model.”  Steve Blank 

There are many definitions of scalability and ways in which the term can be used. For example, in a technical setting, one definition of scalability is: “a measure of the ability of a system to maintain its performance under an increasing load.” In a business setting, the definitions of scalability can vary based on context. Business people who focus on management issues tend to look at scalability differently than people who are financially-oriented. A sales team looks at scalability in yet another way. A CFO might argue that scalability as the ability of the business to grow revenue and profit at an exponential rate while only adding resources at an incremental rate. Some venture capitalists argue that scalability is not present unless the business has the ability to grow revenue to $100 million or more which can justify a venture capital investment.

Given the diversity of views about the definition of scalability, perhaps it is best thought of as a phenomena where “you know it when you see it.” If that is true, what would an optimally scalable business look like? Or instead, what qualities increase the scalability of a business? The remainder of this blog post is a discussion of a dozen attributes which can potentially make a business more scalable. As you read this blog post you may conclude, like I have, that these attributes of scalability are in many cases essentially our old friends from the unit economics equation (CAC, ARPU, Churn, Gross Margin and cost of money) plus free cash flow and some outside frictional forces like government regulation and the laws of physics. You may also conclude, as I have, that no two businesses are exactly alike when it comes to scalability. Each of the attributes of scalability are always in flux, with changes in any one attribute potentially impacting the others. There is no precise formula or recipe that will enable a business to scale, but there are best practices. Every business faces different scaling challenges and opportunities.

Scalable businesses tend to have these twelve attributes:

  1. Customer acquisition cost (CAC) is low in a scalable business since positive word of mouth is strong (i.e., the business benefits from organic customer acquisition) 

Andy Rachleff believes: “If you don’t have exponential word of mouth growth, you don’t have product/market fit.” In terms of staging a successful startup, product/market fit (which is central to the value hypothesis) should precede scaling (which is central to the growth hypothesis). Spending capital on growth before you have a product that people want to buy is essentially a giant bonfire of cash. Steve Blank talks about why scalability is so important in business: “Success isn’t about size – of team or funding. It turns out premature scaling is the leading cause of hemorrhaging cash in a startup – and death. In fact: (1) The team size of startups that scale prematurely is 3 times bigger than the consistent startups at the same stage; (2) 74% of high growth Internet startups fail due to premature scaling; (3) Startups that scale properly grow about 20 times faster than startups that scale prematurely; and (4) 93% of startups that scale prematurely never break the $100k revenue per month threshold.” Ryan Smith the founder of Qualtrics describes this objective simply: “Nail It, Then Scale It.” Too often people try to scale a start-up before they nail it.

The positive customer word of mouth that Rachleff describes is important for a business since it enables a lower customer acquisition cost (CAC). In other words, scalable businesses generating organic growth do not need massive spending on marketing and sales. Every business will have some customer acquisition costs but in the best and most scalable business that cost is relatively low. Bill Gurley agrees with Rachleff: “With great companies the consumers buy because the product is so good. They aren’t spending [tens of millions] on marketing.” Gurley also believes that customers quality if higher is they are organically acquired: “Organic users typically have a higher NPV, a higher conversion rate, a lower churn, and more satisfied than customers acquired through marketing spend.”

It is important to understand that growth is not always organic from the start of a business. Sometimes critical mass must be achieved in non-scalable ways before a business becomes scalable via organic customer acquisition. Paul Graham points out that sometimes doing what does not scale is essential to enabling critical mass which does allow a business to scale: “One of the most common types of advice we give at Y Combinator is to do things that don’t scale. In Airbnb’s case, these consisted of going door to door in New York, recruiting new users and helping existing ones improve their listings.” 

2. Scalable businesses have fewer incremental marginal costs after a modest upfront investment has been made to create the product or service  

Software is the ultimate representation of this second attribute of scalability because it has unique qualities. If you give me your car, you no longer have a car. But if you give me a copy of your software, you still have your software. We don’t necessarily need to be “rivals” about owning the same software, so the term used to describe something like software is “non-rival.” That billions of people can possess the same software at close to zero additional cost on a non-rival basis, combined with the fact that cost of making another copy of software is essentially zero and the cost of distributing that software to customers is also close to zero means that a software business when properly run and possessing the right attributes can deliver almost magical business results. Bill Gates said about the software business in 1993: “It’s all about scale economics and market share.  When you’re shipping a million units of Windows software a month, you can afford to spend $300 million a year improving it and still sell it at a low price.” Once a software business recovers its cost associated with research and development a lion’s share of the additional revenue can drop to the bottom line as profit. The profit potential of software is unprecedented in the history of business. The business outcomes that Google and Facebook represent are examples of this phenomenon. Contrast the scalability of a software business with a home security company that must roll a truck with a trained technician who installs expensive equipment in the home and where a human operator must respond to service calls.

3. A business is more scalable if the total addressable market is enormous  

It is by definition impossible to grow a business significantly if the market is too small. Sequoia’s co-founder Don Valentine said once: We have always focused on the market — the size of the market, the dynamics of the market, the nature of the competition — because our objective always was to build big companies. If you don’t attack a big market, it’s highly unlikely you’re ever going to build a big company.” One slide that venture capitalists almost always see in a pitch deck for a startup is the addressable market slide. Often it is a pie chart depicting a massive total addressable market (TAM) and conveying the point that the business only needs a small slice of that market to be a huge success. For example, here below is a company called Artsy making a case for a large addressable market for its business:

“Despite an estimated $3 trillion of art assets in the world, only $44 billion trades in a given year—and less than 2 percent of qualified buyers participate in this market due to high transaction costs, long lead times, and limited transparency on pricing and value,’ Artsy will bring this last major consumer category online and thereby substantially expand the size of the global art market. We look forward to working with Artsy to make a larger, more connected art market a reality. The global art market is currently valued at around $44 billion annually, and about $3.75 billion of that was spent online in 2016, according to The European Fine Art Foundation, a rise of about 15 percent over 2015.”

4. In a scalable business the average cost of creating the products and/or services fall as the volume of its output increases (economies of scale) 

Supply-side economies of scale exist when there are reductions in the average cost per unit associated with increasing the scale of production for a product or service. JP Morgan’s Jamie Dimon has said that if we didn’t have economies of scale, “We’d still be living in tents and eating buffalo.” Scale economies have always been important but n recent decades scale economies and their impact have been put on the equivalent of steroids. Erik Brynjolfsson explains this phenomenon: “Technology has made it easier for different firms to coordinate their activities with one another, and they don’t have to be part of one company. They can get the benefits of scale without the inertia of scale.”

Scalabilty can be further understood by sorting the attributes of scalability into categories. Venture capitalist Alex Taussig describes the financial aspects of scalability in this way: “Businesses that scale are businesses with operating leverage. Put simply, if you add operating costs (sales, marketing, administrators, R&D, etc.) at the same rate you grow revenue, then your business does not scale. Alternatively, if additional revenue requires relatively smaller and smaller additions to operating costs, then congratulations… your business scales!”

5. A scalable business requires fewer people to operate 

Mike Maples Jr. describes some of the operational aspects of scalability here:

“Company power has to do with technical debt or management debt. So technical debt is sort of like when you make short-term, expedient decisions in the technology that sort cost you later. Maybe in order to ship something on time, you had to cut some corners, and the architecture wasn’t as elegant as it could’ve been, or just the attention to detail or bug fixing maybe wasn’t as good as it could’ve been. And so technical debt is sort of like when you put off some things that you have to solve later, but they cost you more money and time after the fact. And management debt is the same thing, but it’s for lack of having management systems in place. And if you have too much management debt, if the company starts to take off and do really well, you don’t have the internal capacity and wherewithal to scale to the speed that the opportunity might scale.”

Maples uses this approach to looking at a business opportunity which I have written about before:


Fred Wilson describes some of the work required to enable operational scalability in this way: “Investing in management means building communication systems, business processes, feedback, and routines that let you scale the business and team as efficiently as possible.”

The classic example of a non-scalable business is a consulting company since in order for the business to grow it must hire more people the same skills and abilities. Alex Taussig writes: “McKinsey & Co. is one of the greatest consulting firms and brands in corporate America. But, it doesn’t scale. Ignoring its publishing business, McKinsey needs to add consultants, almost on a one-to-one basis, to grow its revenue.” It is time consuming and expensive to create new consultants and they often leave to form their own consulting firms or join a company.

Other business scale very well. It is hard to find a more representative story of the ability of a software-driven business to swiftly rise to fabulous success while employing very few people than the messaging provider WhatsApp, a business famously sold to Facebook for $21.8 billion. The company was founded in 2009 and sold just a few years later in 2014. Wired magazine points out: “One of the (many) intriguing parts of the WhatsApp story is that it has achieved such enormous scale with such a tiny team. When the company was acquired by Facebook, it had 35 engineers and reached more than [one billion] users.” New approaches to programming adopted by WhatsApp enabled scale to be created by the business at speeds that were previously not possible. WhatsApp, Skype, Line and WeChat now dominate messaging, saving consumers billions of dollars in charges. 

6. A business that generates positive float, which creates a low cost source of capital, is more scalable

Bill Gurley and Jane Hodges describe the Dell strategy in a classic article from 1998:

“From a corporate perspective, the best measure of fitness is return on invested capital (ROIC). This measure matters most because over the long haul, capital flows toward investment opportunities with a high ROIC. Inefficient companies, on the other hand, are eventually starved of the cash they need to survive. To understand just how indispensable technology has become, you have to follow the basic math of return on invested capital. To get ROIC, you divide EBIT, or earnings before interest and taxes, by invested capital. Now let’s divide the numerator and the denominator by annual sales. This restates ROIC as operating margin multiplied by asset turnover. In other words, the two components that define a company’s fitness are the ability to charge a high spread between price and actual cost, and the ability to generate sales from a small base of invested capital…. companies that lack competitive information technology will be in serious trouble. They will resemble a 40-year-old trying to win Wimbledon with a small wooden racquet. Their business models may no longer be economically sustainable. Companies like Dell have reached an interesting new stage in the evolution of business–negative working capital. They collect money from customers before they have to acquire components or spend money. This phenomenon allows these companies to grow without raising capital, even if day-to-day profitability is zero.”

Gurley elaborated on Dell’s advantage in another article: “Dell’s incredible five days of inventory allows it to pass on component price declines faster than anyone else in the industry. But perhaps the unique aspect of Dell’s business advantage is its negative cash conversion cycle. Because it keeps only five days of inventories, manages receivables to 30 days, and pushes payables out to 59 days, the Dell model will generate cash–even if the company were to report no profit whatsoever.”

Justin Fox explained the financial benefits further:

“If you have a business where your customers pay you quickly, you manage your inventory well, and you’re able to take your time in paying your suppliers, your free cash flow can be consistently positive even when your net income is not. Which is exactly the kind of business that Jeff Bezos and his colleagues have constructed at Amazon over the past decade. According to my instructor in such matters, Harvard Business School finance professor Mihir Desai, the key metric of a company’s cash-generating prowess is the cash conversion cycle, which is days of inventory plus days sales outstanding (how long it takes your customers to pay you, basically), minus how many days it takes you to pay your suppliers. Super-efficient retailers such as Walmart and Costco have been able to bring their CCC down to the single digits. That’s impressive. But at Amazon last year, the CCC was negative 30.6 days.”

7. In a scalable business pricing power is high, enabling high gross margins and profit 

Warren Buffett believes: “The single most important decision in evaluating a business is pricing power. If you’ve got the power to raise prices without losing business to a competitor, you’ve got a very good business. And if you have to have a prayer session before raising the price by 10 percent, then you’ve got a terrible business.” Charlie Munger has a similar view:

“There are actually businesses, that you will find a few times in a lifetime, where any manager could raise the return enormously just by raising prices—and yet they haven’t done it. So they have huge untapped pricing power that they’re not using. That is the ultimate no-brainer. … Disney found that it could raise those prices a lot and the attendance stayed right up. So a lot of the great record of Eisner and Wells … came from just raising prices at Disneyland and Disneyworld and through video cassette sales of classic animated movies… At Berkshire Hathaway, Warren and I raised the prices of See’s Candy a little faster than others might have. And, of course, we invested in Coca-Cola—which had some untapped pricing power. And it also had brilliant management. So a Goizueta and Keough could do much more than raise prices. It was perfect.”

What companies have pricing power today? Facebook would be one example. In the most recent quarter the average growth in the price of Facebook advertising grew by  24 percent to a record high. What drives pricing power? The sustainable competitive advantage that I wrote about in my blog post on Michael Porter.

8. A business is more scalable if it has few regulatory and legal barriers

Some businesses require approval after approval to grow revenue and profit and are not very scalable. Highly regulated businesses are harder to scale. One highly regulated business that I have experience with is communications satellites. Not only do you need permission to launch satellites but you need agreement of regulators that you can occupy a spot in orbit. use radio frequencies in creating communications links and to operate as a communications provider.

Many other industries have a high regulatory component to their business. The bad new is that businesses with a lot of regulation impacting what they do are hard and expensive businesses to enter. The good news is the same thing, since that difficulty can create barriers to entry.


9. If product and/or service distribution simple and inexpensive (preferably just bits delivered on-line) the product is more scalable

The speed of adoption of a service like WhatsApp has no precedent in the history of business. The cost of delivering bits for that application is tiny. People receive the product on devices that they already paid for.  When a business has attributes like WhatsApp the result can be remarkable:


Chris Dixon has said that it is only a matter of time before a single programmer achieves greater success than WhatsApp in terms of how fast his or her application is adopted. Now, more than ever, one person can literally change the world in a major way since they now have the ability to create software on inexpensive machines, using techniques they can learn on line, by accessing a third party data center in the cloud and delivering the service over the global network of networks. The good news is that barriers to entry in business are disappearing. The bad news is also that barriers to entry are disappearing in business.

10. Maintenance and support costs are low in a scalable business

Many modern software applications can be supported in an automated way, which can make the cost of goods sold (COGS) remarkably low and gross margins incredibly attractive. I wrote about that phenomenon in my blog post on pricing and gross margins. Cloud computing has radically reduced the cost of creating a startup. The good news is that it is cheaper than ever to conduct new business experiments, the bad news is that there are more people and companies than ever conducting these experiments.

11. In a scalable business customer retention is very high (low churn)

My blog post on customer churn is here https://25iq.com/2017/01/27/everyone-poops-and-has-customer-churn-and-a-dozen-notes/ and since this post is already getting a bit long I will not say much more here. What makes a business scalable is a service that is sticky and as a result does not suffer too much from painful churn. Every business has some customer churn, but some have less than others. The best businesses understand the value of customer retention and as a result have effective ways to keep the impact of churn manageable.

12. In a scalable business network effects are strong, which increases the value of the product or service as the number of customers grows 

My post on network effects is here https://25iq.com/2016/03/24/two-powerful-mental-models-network-effects-and-critical-mass/ and again I won’t write too much more now since this post is running long.

I will add one final note before concluding this post. Investors should consider both supply-side and demand side scalability in evaluating the financial prospects of a business. Supply-side scalability concerns the ability of a business to use capital, labor and resources more efficiently as the business grows. Managers concerned with supply-side scale are working to optimize processes so profit can be maximized. Sangeet Paul Choudary writes:

“Optimization involves creating repeatable processes which can be cost-effectively repeated over and over again to grow the business. The two key aspects of scaling are:

A) Repeatability

B) Cost-effectiveness

A lot of business education is focused on strategies for optimization of these processes. An IT outsourcing shop, for example, optimizes processes surrounding the labor variable to create scale. A manufacturing business has to optimize processes involving procurement, production, distribution.”

Scalability on the demand side, which is where network effects happen,  can be created by structuring how customers interact with the product and with other users of the product.

Network effects exist when the “value” of a format or system depends on the number of users. These effects can be positive (for example, a telephone network) or negative (for example, congestion). They can also be direct (increases in usage lead to direct increases in value to users, as with the telephone) or indirect (usage increases the production of complementary goods, as with cases for mobile phones).

Investors seek a business with network effects since it has attributes which can help it build a barriers to entry against competitors.

















What Would a Healthy Music Streaming Business (e.g., Spotify, SoundCloud, Pandora) Look Like?

SoundCloud was just recapitalized by investors in a dramatic down round after announcing that the company had only enough cash to last into the fourth quarter. Pandora just agreed to terms on a new investment that was also a down round and which resulted in a new controlling investor. Both companies have a new CEO. More broadly, there are bitter fights in the value chain between music streamers and music owners about royalty rates. All is not well in some parts of the music distribution business. Change is needed. As Jimmy Iovine puts it: “Not every industry was meant to last forever. The record industry needs to do something that artists can’t do for themselves. Or else there’s no reason for it to exist.”

This blog post will follow the Charlie Munger “inversion” approach. Instead of focusing on what is wrong with the finances of companies like SoundCloud, Spotify and Pandora (“SSP”), this post will focus on what they would have to do right to create a profitable business. The question that I want to answer in this blog post is: What would a healthy music streaming business look like for SSP? As my friend Bruce Dunlevie likes to say: “What can go right?”

In thinking about these issues it is important to remember that streaming is not a business, but rather a technology. Streaming is just one method of distributing music. Another point to keep in mind is that no business can be healthy if it does not have sound unit economics. There are zero exceptions to this rule.

The healthiest business that has somewhat similar characteristics to SSP is Sirius XM. It is a rough analogy, as we will see, but it is worth thinking about. How can music streaming by SSP be more like Sirius XM?

Let’s take a look at the unit economics of Sirius XM using a recent reports:

Subscriber Acquisition Cost (SAC)       $31

Gross margin                                          62%

ARPU:                                                      $13.22

Churn:                                                     1.7% a month

Assuming a 10% discount rate in this LTV calculation, the Sirius XM unit economics look like this:

XM unit economics

Sirius XM has a very attractive business which is creating real value.

It is worth remembering that the deal Liberty struck to acquire the stake in Sirius XM was well timed. It was 2009 and due to the turbulence created by the financial crisis, cash was king and Sirius XM desperately needed it. Liberty loaned $530 million to Sirius XM in return for a ~40% equity interest just in time:

Sirius XM, the embattled satellite radio company, said early Tuesday that it reached an 11th-hour deal with Liberty Media that will allow it to repay maturing debt and avoid a bankruptcy filing, at least for the moment.” https://dealbook.nytimes.com/2009/02/17/sirius-xm-reaches-loan-deal-with-liberty/

Liberty was buying into a company that had already done much of the really painful parts of creating a business that necessarily has huge upfront capital costs. For example, the $6 billion in accumulated net operating losses had been funded by other investors. In a recent earnings call Sirius said that these net operating losses mean no taxes will be paid until at least 2018. The free cash flow generated by the business has allowed them to do share buyback and pay dividends at a rate of about $2 billion a year.

As an aside, I ran into Liberty President and CEO Greg Maffei in Sun Valley at the bottom of a chair lift in the spring of 2009 shortly after they first bought a stake in Sirius XM. I remember telling Maffei that his purchase was an amazing bargain. I knew the satellite business well since I was an early Teledesic employee, was part of the negotiations with Rupert Murdoch over his Death Star satellite plans, did due diligence on Iridium, Globalstar and most importantly know about satellite radio since McCaw Cellular Communications had been a shareholder in American Mobile Satellite since its creation. I wish I had loaded up on more Sirius XM stock at that time. More recently, other investors have reached this same conclusion. For example, Berkshire Hathaway has invested in Sirius XM’s business both directly and through their equity investment in Liberty.

The beauty of the Sirius business model is obscured for some people by the fact that subscriber acquisition cost (SAC) is an upfront expense (see the number in red above in the spreadsheet screen shot). Current quarter GAAP “earnings” do not fully reflect the annuity-like value that is being created by a company like Sirius or Amazon. In other words, in a growing business that has up front SAC current quarter earnings are lower. The good news about that timing of the customer acquisition expense in a growing business that is creating annuity value is it defers taxes with further compounds the wealth that is being created.

The attributes of John Malone’s preferred business model have been consistent over the years and exist in the case of Sirius XM.


Many other companies like Amazon have adopted the financial model pioneered by cable television pioneers like John Malone and my friend Craig McCaw.

How can the SSP music streamers become more like Sirius XM? First and foremost, they must start working to improve each of the unit economics variables and become more like Sirius. These variables discussed below are all important, but nothing is more important for the SSP music streamers than improving gross margin (#2).  Without a gross margin fix, nothing else matters.

  1. Subscriber Acquisition Cost:    

At the time of the launch of the satellite radio business subscriber acquisition cost (SAC) was high. There were two separate satellite radio systems, Sirius and XM Satellite Radio and each was bidding against the other for distribution. They also signed expensive content deals that were not sustainable. For example, Sirius’ SAC during the first quarter of 2003 was $299. Ouch! The manufacturing volumes on the receivers were low and so unit cost were high. The adoption by car buyers of the service was also relatively low and brand awareness was still being created who was too often addressed via expensive advertising. Cars with radios were not yet in the used car channel where SAC can be lower. Both satellite radio providers did what they could to improve their sales funnels, improve retention and lower SAC but they had a long way to go. By 2007 Sirius’ SAC had dropped to $105, but it was still very financially painful. The merger of Sirius and XM in March of 2008 was a helpful event that caused SAC to drop further. With the help of Liberty SAC has continued to drop over the years until now it is $31 (which is an average figure that includes both higher SAC new car customers and lower SAC used car owners).

Sirius has acquired its more than 32 million subscribers in a number of ways. The biggest driver of SAC is the installation of new radios in cars on speculation that conversion rates will be high enough. When a new car leaves the dealer it typically comes with a free trial, which lasts three months. That free radio and trail is COGS that is really CAC but it works to get people hooked. Sirius XM is not a big advertiser and spends money instead on getting better content.

Sirius XM is in about 75% of cars and conversion is ~40% of that figure.

“conversion of new car buyers remains our largest single acquisition channel, in the second quarter these represented only 46% of all self-pay gross additions, compared to 48% a year ago and 49% the year before that. This means that 54% of our gross adds are coming from the existing fleet, either our used car efforts, win-back, self-pay activation or aftermarket additions. We only expect this share to climb higher in the future as our penetration rate in used car sales increases from about 34% in the second quarter to eventually match the approximately 75% penetration in the new car market.”

The bottom line is that Sirius XM’s SAC can be what it is because ARPU and gross margins are high and churn is low. Music streamers like SSP do not have that luxury. The ad supported ARPU for a SSP music streamers is tiny. Some reports indicates that SoundCloud ARPU is just 11 cents per user. XM has zero ads on its music channels. Total advertising revenue at Sirius XM is about 2%. It is not really a material part of the business of Sirius XM.

At a Morgan Stanley conference in 2015 Sirius XM’s CEO Jim Meyer said:

  • “Economics on used cars are compelling, don’t pay a subsidy on second or third owner, only new car
  • There’s not any technology that will go on the vehicle that SIRI won’t also be able to use
  • We won’t have commercials on our music channels, never will
  • Future of SIRI is based on subscriptions, not advertisement
  • We don’t want to get into video delivery, or compete with Netflix (NFLX), we want an acquisition that will make subscriber base stronger, lower the churn, grow ARPU, etc. We don’t see the streaming business models right now as good businesses, not good economics.”

Sirius XM has been very opportunistic in working its sales funnels and churn management procedures and practices.  It has partnerships with used car dealers, auto lube stores, insurance companies, banks and other businesses to generate leads.

There are other opportunities and challenges ahead. How do they sell more service to younger consumers? How do they sell service to people who do not own a car? How can they use music streaming to lower SAC for the paid service? Sirius’ CEO and President Greg Maffei made this comment about Liberty’s investment in Pandora recently:

“The $480 million we invested [in Pandora] will not move the needle at Sirius. It’s really there about figuring out is there a strategy in which we have a free offering that Pandora can be a part of that story that we can together figure out how to better monetize these 75 million to 80 million monthly users that they have in a more integrated fashion with the Sirius higher price offering.”

Maffei is talking about the value of an up-sell approach.

SSP music streamers have no choice but to be upselling first party premium content as will be explained next. The problem the music streamers face on SAC is that the amount of SAC that can be justified given their current gross margins and ARPU is miniscule. If SSP raise SAC then they will end up with a lot of customers who don’t really like the service that much. Not only are customers acquired organically cheaper to acquire but they are of higher quality and churn less. No one understands this better than Jeff Bezos:

 “The balance of power is shifting toward consumers and away from companies…the individual is empowered… The right way to respond to this if you are a company is to put the vast majority of your energy, attention and dollars into building a great product or service and put a smaller amount into shouting about it, marketing it. If I build a great product or service, my customers will tell each other….In the old world, you devoted 30% of your time to building a great service and 70% of your time to shouting about it. In the new world, that inverts.” “Your brand is formed primarily, not by what your company says about itself, but what the company does.”

 2. Gross Margin:          

The royalty paid by Sirius XM for music is favorable for historical reasons. The traditional business model for recorded music was based on the assumption that radio stations playing songs sold records that music labels created and the labels paid the musicians. Only song writers received a royalty from broadcasters since they could not sell records. But when music went digital, the music industry business model flipped on its head and there was no longer much of a business selling physical records. Musicians shifted to making their profit on concerts.

Sirius XM pays 11% of its gross revenue as a royalty to musicians as determined by a copyright board operated by the Library of Congress. What this royalty rate means is that even though it pays for its own content like Howard Stern Sirius XM is able to generate gross margins of ~62%.  Barron’s explains:

Most of Sirius’ content, including Major League Baseball games and Fox News, is signed through the end of the decade. Howard Stern and the National Football League—admittedly costly programming—are up for renewal at the end of 2015. Music channels, which make up about half of Sirius XM’s content, generate an estimated 60% of the costs.

What does this say about what the SSP must do? Here is how one analyst looks at the comparison of Sirius XM to the SSP music streamers:


Pandora reported in the Earnings Conference Call on July 31, 2017:

Subscription ARPU was $4.82 up from $4.76 in 194 the prior quarter, reflecting a shift from Pandora Plus to Premium. For the quarter, licensing cost per subscriber (or LPU), was $3.11, an increase of 5% from Q1. Non-GAAP gross margin was 36%, compared to 38% in the year-ago quarter. The decline in margin year-over-year was primarily driven by higher statutory rates under direct-deals versus statutory rates.

$3.11/$4.82 means the royalty expense alone eats 64.5% of revenue. Ouch!

For Spotify the royalty payments also crush its gross margins. One estimate is:

“84% of Spotify’s total [revenue] last year went back out the door to the music industry, or to facilitate its payment to the music industry.”

“Cost of royalties and revenues paid: Spotify will pay at least $2 billion in payments to record labels, in addition to per-stream rates the company pays when users listen to songs. Dividing cost of revenue — which are primarily royalties paid — by total revenue, nearly 85% of Spotify’s revenues go toward royalty rates.”

Comparing the SSP music streaming gross margins to Sirius XM makes a clear point: the SSP music streamers must get their content costs under control. I like to say that all the LTV variables are interrelated. But the current gross margins are the clear business model killer in the case of the SSP music streamers. Bill Gurley describes my view below:

“a rope connects them all, and they are all facing different directions. When one horse pulls one way, it makes it more difficult for the other horse to go his direction. Tren’s view is that the variables of the LTV formula are interdependent not independent, and are an overly simplified abstraction of reality. If you try to raise ARPU (price) you will naturally increase churn. If you try to grow faster by spending more on marketing, your SAC will rise (assuming a finite amount of opportunities to buy customers, which is true). Churn may rise also, as a more aggressive program will likely capture customers of a lower quality. As another example, if you beef up customer service to improve churn, you directly impact future costs, and therefore deteriorate the potential cash flow contribution. Ironically, many company presentations show all metrics improving as you head into the future. This is unlikely to play out in reality.”

The SSP music streamers must find first party content that does not expose them to wholesale transfer pricing power of content owners to remedy the gross margin problem. Otherwise wholesale transfer pricing power of the record companies means that the SSP streamers will forever be unprofitable. Netflix and Amazon know this and that is why they create first party content.

The work of musicians is not substitutable. For example, Arctic Monkeys are not a substitute for Bob Dylan. The SSP’s music streamers will never have acceptable gross margins until they have their own content. Amazon know this and has a business model focused on generating cash flow only indirectly on music.




3. ARPU:

Sirius XM ARPU has risen slowly and gradually. This is the variable over which Sirius XM has the most control. In contrast, an advertising supported music streaming business the ARPU challenge is not a truly hard variable to control but not very significant in size. The price of an advertisement is so low due to exploding supply that the advertising-supported ARPU of a music streamer is inevitably tiny.

Contrast an advertising supported model to Sirius XM which makes clear that it is cash-money paying subscribers that drive the profit and cash flow train:

“We offer trials to car buyers and we even discount onboard or retained subscribers, but at the end of the day if you don’t want to pay for our service, we don’t have a place for you.”


Sirius XM put the comparison this way at a Merrill Lynch TMT Conference in June of 2005:

Pandora is monetizing at about $11 a user, Clear Channel at about $13, Spotify at about $30 and pays 2/3 of economics in royalties, and we monetize at $150 per subscriber.

The Sirious XM example show that the question for a music streaming company like SoundCloud is: what first party services would people be willing to pay a subscription fee for? What original content is valuable enough to get people to pay a fee? I don’t see any other choice than to do what Netflix did which is increase first party content. This means that SSP must shift from being only content distributors to being, at least in part, content creators/owners.

4. Churn:     

The news on churn has been increasingly good for Sirius XM in recent quarters. In the most recent earnings call the company reported:   

“Churn was 1.7% in the quarter, down from 1.8% in the prior-year quarter. And reductions in voluntary churn rates more than offset pressure from an increasing rate of vehicle related churn. Healthy gross additions and this extremely good churn performance produced 466,000 net new self-pay subscriber additions in the second quarter which brought the self-pay subscriber base to nearly 26.7 million and total subscribers to just over 32 million.”

Churn is super important in any subscription business. Sirius XM said in an earnings call in 2015: “When you have subscriber base as big as SIRI, a 0.10% change in monthly self-pay churn is equal to the difference between 70,000 subs in a quarter or 280,000 net subs in a year.” Every single basis point of churn is important for anyone in the services business. The best way to grow is not to shrink.                                  

Less than 3% churn for a consumer service can be a healthy phenomenon depending on the other variables. Lower than 2% churn is great and lower than 1% churn is outstanding. The level of churn is a product of a number of factors like high product/market fit and sound business execution on retention processes like automatic renewal.

What about churn at the SSP music streamers? One report is as follows:

“Apple Music have a subscriber churn rate of 6.4%, which is nearly three times higher than Spotify, whose churn rate is 2.2%.”

The best way to retain customers is always to have a fantastic product. Of course there are a range of operational excellence approaches like automatic renewal that can help, but in the end a great service is the most effective way to retain a subscriber. The best way to increase satisfaction is not, as Pandora has done, to increase ad loads.  A far better approach would be to have content that is compelling enough that people do not leave. XM Sirius has this hook in the Howard Stern Show and other first party content. The SPP music streamers must find something similar that is first party. There is no other option.

I am going to stop this discussion here since the post is getting a bit long. Most people do not have the patience for an analysis like this which I could have made much longer. Getting the data needed to value a stock is like being a detective. You must find data from many places, figure out what is signal and what is noise and then put together an analysis despite inherent uncertainty. If you do not find this process fun or are unwilling to do the work, you should be buying shares in the form of a low cost index.



https://www.fool.com/investing/2017/04/14/so-much-for-sirius-xm-buying-pandora.aspx http://www.hollywoodreporter.com/thr-esq/did-siriusxm-pull-a-fast-one-major-record-labels-a-deal-suing-indie-musicians-992733
















A Dozen Lessons about Product and Services Pricing (Including being “Too Hungry to Eat”)

This is a blog post about some of the most basic elements of pricing a product or service. Since the longest a post like this should be is about 3,500 words, the scope of what is covered here must be significantly narrowed. This discussion therefore focuses mostly on the sale of a single product or service and on the right price point. Decisions get more complex when there are multiple offerings with different price points for different features and you are thinking about upsell, cross sell, negative churn etc.

As context, I have written many other blog posts already about topics related this post including:

  1. Product/market fit: https://25iq.com/2017/02/17/a-dozen-lessons-about-productmarket-fit/
  2. Steve Blank on business models https://25iq.com/2014/10/18/a-dozen-things-ive-learned-from-steve-blank-about-startups/
  3. Eric Ries on Lean Startups https://25iq.com/2014/09/28/a-dozen-things-ive-learned-from-eric-ries-about-lean-startups-lattice-of-mental-models-in-vc/
  4. Growth: https://25iq.com/2017/02/10/a-dozen-lessons-on-growth/
  5. Customer Acquisition Cost (CAC) https://25iq.com/2016/12/09/why-is-customer-acquisition-cost-cac-like-a-belly-button/
  6. Churn https://25iq.com/2017/01/27/everyone-poops-and-has-customer-churn-and-a-dozen-notes/
  7. Freemium: https://25iq.com/2017/04/22/the-rise-of-the-freemium-business-model/
  8. Multi-sided markets: https://25iq.com/2016/10/22/a-dozen-things-ive-learned-about-multi-sided-markets-platforms/
  9. Network effects: https://25iq.com/2016/03/24/two-powerful-mental-models-network-effects-and-critical-mass/
  10. Subscriptions: https://25iq.com/2017/07/15/amazon-prime-and-other-subscription-businesses-how-do-you-value-a-subscriber/

This post will be number 11 in this series and a post next weekend on scalability will be number 12. That will result in the series of 25IQ blog post fitting the usual dozen lessons template.

The first focus of any startup founder should be to prove the validity of a value hypothesis. If a business does not make a product or service that customers are willing to pay money for, nothing else matters. Anu Hariharan, who is a Partner with the YC Continuity Fund writes:

“A great way to waste money, resources, and jeopardize the future of your company is to invest in a growth program before you’ve proven you can retain customers. In other words, it’s best not to hire a full-fledged growth team to put major ad dollars into growth until you’ve ensured you don’t have a ‘leaky bucket’ problem.’”

The amount of unique value delivered by a new business should be significantly more than the established competition if a startup wants to be successful. If the value delivered by the business is “me too” relative to existing competitors the competitive environment will be is more than hard for a startup.

Only after the value hypothesis has been proven should the startup focus on a growth hypothesis. A key part of the growth hypothesis is the business model and a key part of that is pricing. The question of pricing raise many issues, one of which Marc Andreessen addressed recently:

“At the growth stage, when a startup is fully in market and building out sales and marketing efforts to expand, the decision [to invest] becomes far more about the financial characteristics of the business—particularly unit economics: can the startup profitably sell its product to each customer?… we see far more SAAS startups underpricing their product than overpricing.

The problem with overpricing seems obvious—we in our daily lives as consumers are more likely to buy products if they are cheaper, and so pricing higher is presumed to reduce sales.

But that’s not how business markets tend to work—in business markets, where customers make what’s called a considered purchase, the result of a reasonably objective and rigorous analysis of options, startups that underprice tend to have the problem I call “too hungry to eat”—by pricing too low, they can’t generate enough revenue per deal to justify the sales and marketing investment required to get the deal at all. In contrast, by pricing higher, the startup can afford to invest in a serious sales and marketing effort that will tend to win a lot more details than a competitor selling a cut-rate product on a shoestring go-to-market budget.”

There are many types of businesses and each has unique attributes that are in a constant state of change. There are an endless number of permutations of the relevant variables and the systems involved in the business. Nothing remains the same and everything is always in flux. That is no small part of what makes business so interesting to me.

This post can’t possibly discuss pricing optimization for every type of business since there is so much variation. For example, gross margins can vary greatly depending on the sector involved (DM means developed markets). But general principles and best practices can be discussed. Gross margins are a very important part of creating an optimal pricing strategy:

gross margins

I don’t want to insult anyone reading this but I don’t want to leave anyone behind either (this tension between expert readers and novices is always a challenge in writing these posts). What’s a gross margin? Lighter Capital provides an example:

“ABC Company buys Widgets for $1 and can sell each Widget for $10. On each sale, they make $9. The gross margin for this company is 90%. On the other hand, XYZ Company buys Thingies for $5, and sells each Thingy for $10.

ABC Company

XYZ Company

Sale (One Unit)



Cost of Goods Sold



Gross Profit



Gross Margin



Assuming all else is equal, ABC Company has a higher margin on their sale (90% vs 50%)..”

To further make the discussion in this blog post more manageable by limiting its scope I will mostly focus the text that follows on a “software as a service” business (SaaS). Gross Margins in public SaaS companies look like this according to data compiled by venture capitalist Tomas Tunguz:


“…investors prize SaaS companies because providing SaaS service costs very little, and consequently these startups record very high gross margins. The median gross margin for publicly traded SaaS companies expands from 50% in year four to just under 75% in year five, as the chart above shows.”

Why are gross margins so high in SaaS? The answer is explained well by Andreessen Horowitz in a blog post:

“Paraphrasing Jim Barksdale (the celebrated COO of Fedex, CEO of McCaw Cellular, and CEO of Netscape), ‘Here’s the magical thing about software: software is something I have, I can sell it to you, and after that, I still have it.’ Because of this magical property, software companies should have very high gross margins, in the 80%-90% range. Smaller software companies might start with lower gross margins as they provision more capacity than they need, but these days with pay-as-you-go public cloud services, the need for small companies to buy and operate expensive gear has vanished, so even early stage companies can start out of the gate with relatively high gross margins”

Bill Gurley lays out the value of high gross margins for a business here:

“There is a huge difference between companies with high gross margins and those with lower gross margins. Using the DCF framework, you cannot generate much cash from a revenue stream that is saddled with large, variable costs. …Selling more copies of the same piece of software (with zero incremental costs) is a business that scales nicely. Companies that are increasing their profit percentage while they grow are capable of carrying very high valuation multiples, as future periods will have much higher earnings and free cash flow due to the cumulative effect of growth and increased profitability.”

 Bill Gates in 1993 described what Bill Gurley is talking about in this way:

“It’s all about scale economics and market share.  When you’re shipping a million units of Windows software a month, you can afford to spend $300 million a year improving it and still sell it at a low price.”

One useful way to better understand the context and implications of what Andreessen, Gurley and Gates are saying is to follow the Charlie Munger approach and “invert” the analysis. If a SaaS  business has 60-90% gross margins it has headroom “below the gross margin line” to spend on these three expensive and unavoidable aspects of their business:

  1. Research and Development (R&D)
  2. General and Administrative (G&A)
  3. Sales and Marketing. (S&M).

What I typically do when considering the economics of a business is perform a “reverse math” analysis of business financials using well-known benchmarks. Like almost every other business, the SaaS company will have familiar categories of expense. To illustrate, I will use an example of a specific software as a service (SaaS) business serving enterprise markets which recently went public so we have access to an IPO that is not too dated. MuleSoft’s financials in that document include this chart:


You can see that MuleSoft’s gross margin was 74% in 2027.  Tomas Tunguz notes that MuleSoft’s gross margin:

“is better than the public software average of 71%. Professional services margins used to be -25%, but the company has brought that figure up to breakeven in the last year. This may also be a contributing factor to the increase in average contract value.

mule inc

Mulesoft is rapidly approaching cash flow from operations breakeven and net income profitability. Cash flow from operations breakeven means the business generates as much cash as it consumes setting aside financing and investing activities. Mulesoft operated with an estimated sales efficiency of 0.57 in 2015 and a estimated sales efficiency of 0.63, which implies a payback period of 19 months, right on the average.”

MuleSoft’s R&D and G&A alone are 35% of revenue, which leaves less room for spending on sales and marketing needed to grow the company. Every business has general and administrative costs. To illustrate:

mule GA

Every SaaS business also has R&D costs (this cost can range between 10 and 30%nd should drops as the company matures and is operated more effectively).

“In general, R&D expenses (as measured as a percent of revenue) for public SaaS co’s are lower than traditional licensed software companies.  Unlike licensed software vendors, SaaS companies are not required to support multiple technology stacks (i.e., operating systems, Web servers, databases, etc.) or a variety of hardware platforms.  Additionally, SaaS solutions are typically version-less (all customers are on the same version) thereby enabling critical R&D dollars of the organization to focus on the next version and innovation.”

The next item on the list of below the gross margin line expenses is sales and marketing. This is an expense that can easily kill a business or make it a winner. The very best companies have products that sell organically. Bill Gurley writes:

“All things being equal, a heavy reliance on marketing spend will hurt your valuation multiple. …You will be hard pressed to find a company with a heavy marketing spend with a high price/revenue multiple. This should not be read as a blanket condemnation of all marketing programs, but rather a simple point that if there are two businesses that are otherwise identical, if one requires substantial marketing and one does not, Wall Street will pay a higher valuation of the one with organic customers.” Organic users typically have a higher NPV, a higher conversion rate, a lower churn, and more satisfied than customers acquired through marketing spend.”

As an example of how complex pricing issues can be, another important pricing issue is how a price will impact customer acquisition costs (CAC) and churn. I’ve been involved in setting services prices since there were zero portable mobile phones in service. That is a long time ago. One thing I have learned over the decades is that the higher the price and the longer the contractual commitment, the higher customer acquisition cost (CAC) and churn will be. If this were not the case all customers would be signing up for >10-year binding contractual commitments. People do not like to give up optionality by signing long terms contractual commitments, so sales incentives (e.g., price discounts) and higher sales and marketing costs are often required in order to get a longer customer commitment.

As another example of the complexity of pricing issues, when founders talk about SaaS they often assume the revenue is recurring. Many founders who think that they have recurring revenue really have 12-month deals. While this normal early on, especially for a pilot, it isn’t annual recurring revenue (ARR) if it is just payment spread over a year. This is especially true if there is no per-time period and per-user price. Until there have been renewals what is “recurring” in ARR is unknown.

Yet another issue is the topic of freemium or selling religious icons to the already converted. This can be a useful strategy to reduce CAC.  But you need to be careful since freemium results in higher COGs, which is hidden CAC. If you give away storage to get sales leads that isn’t really COGs now is it. It is just a different sort of sales and marketing spending.

What are most SaaS companies spending of sales and marketing? Tomas Tunguz writes:

“…In the first 3 years, these public SaaS companies spend between 80 to 120% of their revenue in sales and marketing (using venture dollars or other forms of capital to finance the business). By year 5, that ratio has fallen to about 50%….”


How should a SaaS company find the right price points for its services? They are best discovered through actual interaction with customers and a series of pricing experiments. The right price is discovered through a carefully constructed but inevitably slightly trial and error process. For example, a startup might start with its first paying customer and set a price. As the startup reels in new paying customers the business can gradually raise prices as it grows its customer base but only until it meets significant resistance on price.

This gets us to the related issue of setting price for a new category of SaaS. What I tell founders is that the best way to price of a new service that customers have not seen before is to set price so it produces sufficient gross margins so that the business has a margin of safety.  I like to see a business set a target of at least 70% gross margins on SaaS. It can be lower at the start of the effort but there must be a plan to get it higher. An 80% gross margin would be better obviously.  If a business can’t eventually get to a point where the business generates a 70% gross margin in a SaaS business it really needs to think hard about whether it has achieved sufficient product/market fit. A gross margin of 60% is living more dangerously obviously. Of course, most business have far lower gross margins than a SaaS business as was noted in the Median Gross Margins by industry chart above. But the more general point remains true for any business: if a startup is not able to generate better than industry standard gross margins it very likely does not have sufficient product/market fit.

Reid Hoffman believes:

People underestimate how much of an edge you need. It really should be a compounding competitive edge. If your technology is a little better or you execute a little better, you’re screwed. Marginal improvements are rarely decisive.” “The question comes down to…not to think of it just as a question of ‘Oh, I have a better product, and with a better product, my thing will work, as opposed to other things.’ Because unless your product is like 100x better, usually your average consumer…they use what they encounter. If other[s] are much more successful at distribution and they have much better viral spread, they have better index and SEO…it doesn’t matter if your product is 10x better, the folks don’t encounter it.”

If you deliver this sort of value, you can set your price on a value basis. Lincoln Murphy of Sixteen Ventures writes:

“The definition of Value Pricing is: Applying a price to a service that is congruent with the value derived from the service rather than the underlying cost to create and deliver the SaaS, market prices, specific margins, etc. Which makes Value Pricing the most effective method of pricing for SaaS and Web Apps… something like cost+margin just doesn’t make sense. The key to Value Pricing is knowing the, well, value of your service as perceived by your target market AND/OR market segments (not all are alike) … If I sell something for $100, I want to provide at least $1,000 in value to them… at least.”

As an example from another industry, let’s look at the New York Times which has gross margins that are typically about 62%. The New York Times has a yearly average revenue per user (ARPU) of  ~$140 which is ~ $11.66 a month.


Churn and CAC are known only to the management of the New York Times which means investors must guess at what they are to calculate unit economics. My post on unit economics is here. 

The New York Times, like other businesses, periodically conducts pricing experiments to see what it pricing power is. What is tested in these experiments is what Warren Buffett calls is  “pricing power” of the business. Buffett’s famous quote on this topic is:

“The single most important decision in evaluating a business is pricing power. If you’ve got the power to raise prices without losing business to a competitor, you’ve got a very good business. And if you have to have a prayer session before raising the price by 10 percent, then you’ve got a terrible business.”

What determines pricing power? Whether the business has a sustainable competitive advantage, a topic that I wrote about in my blog post on Michael Porter. https://25iq.com/2013/08/26/a-dozen-things-ive-learned-about-strategy-business-and-investing-from-michael-porter-2/ and this post I wrote about Charlie Munger. https://25iq.com/2015/10/10/a-dozen-things-ive-learned-from-charlie-munger-about-moats/

Setting and managing prices is both an art and a science. Having a top rate data science team and some people who have real world experience are both invaluable. Many interacting variables are involved even before you start calculating and managing the business against metrics like lifetime value (LTV). The best way to learn the art and prefect the science is to actually create pricing plans for a business it in a real business setting. In setting and managing prices there are best practices, but there are no precise formulas. The more you do it, the more skill you will acquire.














A Dozen Lessons about Angel Investing from Jason Calacanis (Poker Edition)

This is the last post in my trilogy on how games of chance can teach lessons about investing and business. This first two were:

Ed Thorp: https://25iq.com/2017/07/22/a-dozen-lessons-on-investing-from-ed-thorp/

Poker and Investing: https://25iq.com/2017/07/29/a-dozen-lessons-about-business-and-investing-from-poker/

Blog posts about people are always more interesting and Jason Calacanis is nothing if not interesting. He is an entrepreneur and active angel investor (2-3 startups per month). He also created the six-year old podcast This Week in Startups and the Launch Festival. Calacanis is the founder and CEO of Inside.com, a real-time mobile news app. Calacanis co-founded and was the CEO of Weblogs, Inc., a network of weblogs that was sold to AOL in 2005. He is the author of a new book: Angel: How to Invest in Technology Startups-Timeless Advice from an Angel Investor Who Turned $100,000 into $100,000,000.  If there is one word that jumps to mind when I hear his name it is “hustle.” Calacanis is relentless and he works hard.

Venture capital investing is not gambling since it is a net present value positive activity. Venture capital speculation is gambling, since it is a net present value negative activity. With venture capital investing you can impact the outcome (i.e., change the odds) by having skill. You are also playing against other people not just the house. Professionals like Calacanis are investors since they actively impact the outcomes in a positive way by having a high degree of skill in sourcing, picking and helping founders make the business successful. Amateur Angel investors are in contrast to investors like Calacanis often gambling. One way for amateur Angel investors to improve their prospects is to get in the sidecar of a professional Angel investor, which can be accomplished through syndicates with a professional venture capital investor in the lead role.

Richard Zeckhauser in one of his classic papers entitled “Investing in the Unknown and Unknowable” describes the sidecar strategy:

“Most big investment payouts come when money is combined with complementary skills, such as knowing how to develop real estate or new technologies. Those who lack these skills can look for ”sidecar” investments that allow them to put their money alongside that of people they know to be both capable and honest.

…Maxim A: Individuals with complementary skills enjoy great positive excess returns from Unknown and Unknowable investments. Make a sidecar investment alongside them when given the opportunity.”

The usual dozen lessons are below:

  1. “Poker is a real good analogy for angel investing because of implied odds.” “You have to bet, bet, bet with ice in your veins: knowing that after dozens of failures, you’ll hit a winning bet of epic proportions.” “We want 7 of 10 to fail because that means they are trying high-variance projects that have massive implied odds.”

David Sklansky writes in his book The Theory of Poker: “Implied odds are based on the possibility of winning money in later rounds over and above what is in the pot already. More precisely, your implied adds are the ratio of your total expected win when your card hits to the present cost of calling a bet.” Chamath Palihapitiya pointed out that the in a tweet: “Founders + VCs thrive on the implied odds from financings but don’t realize it also comes with reverse implied odds!” He links to this from a web site called The Poker Bank: “Reverse implied odds are the opposite of implied odds. With implied odds you estimate how much you expect to win after making a draw, but with reverse implied odds you estimate how much you expect to lose if you complete your draw but your opponent still holds a better hand.”

Regarding Poker and venture capital generally, Fred Wilson wrote the classic post:

“Early stage venture capital is a lot like poker.  The first round is the ante.  I think keeping the ante as low as possible is a good thing.  I like to think of it as an option to play in the next round and to see the cards.  Clearly, we don’t ante up to just any deal, but it is very useful to think of the first round as the ante. For the first year or 18 months, however long the first round lasts, you get to ‘see your cards’.  You learn a lot about your management team.  You learn a lot about the market you’ve chosen to go after.  You learn about the competition and a whole lot more. Then you have to decide whether to you want to see ‘the flop’, that is the next year to 18 months.  The price to see that is usually higher.  If you don’t like your cards (ie your management team, your market, the competitive dynamic, etc) then you fold.  Cut your losses.  Preserve your capital.  Wait for the next deal.”

 In an interview in San Jose Mercury-News venture capitalist Joe Lacob said about poker:

“No matter how much analysis you do, there’s always going to be things you don’t know. “And what makes somebody good at this business, vs. somebody not good, is the ability to take risk. Calculated risk. And to be OK with that. To be a gambler, to some extent. I like poker. I like the idea… of calculated risk. Doing my homework, and then you have to take a shot. You learn a lot in poker about people. Phil Hellmuth is a good friend of mine and you learn a lot about people when you play that game.”

  1. “I put $25k or $250k into a company and own one to five percent and most of them fail. So that one to five percent times is usually, 8 of 10 times, worth zero. Then one hand you kind of chop it. Then, hopefully, one hand out of 50 becomes Thumbtack or a Wealthfront. Then sometimes you hit the royal flush like Uber. I was the third or fourth person to invest in Uber and it only takes one of those to kind of make your career. Those are the equivalent of a 5,000 to 10,000 times return.”

What Angel investors accept in a business that has not proven either a value hypothesis or a growth hypothesis is far greater outcome variance due to convexity. Venture capitalists  hedge variance/convexity with a portfolio of bets and that is especially true at seed stage. All you can lose financially in venture capital is what you invest and your upside can be more than 1000X of what you invested. Why is an early stage opportunity to invest in a company like Lyft even available? Because most people like the safety of the herd and shy away from risk and uncertainty. Calacanis says:  “I have a theory about angel investing, which is basically you’re investing in the person and that the more outlandish the idea is, and the less people understand it, the greater the chances you should invest in it are.”

  1. “You have to get very comfortable with the concept of losing seven, eight, nine out of 10 bets.” “It’s very hard to sit down at a poker table or a blackjack table where you lose eight or nine out of 10 hands.” “You have to deal with bad news constantly. The companies that are failing take 10 to 50 times more of your energy and emotion and time than the winners. If you are emotionally not resilient, it is not the job for you. Every day, there’s three or four phone calls from founders that come in, or emails us, that they’re running out of money, they’re fighting with their co-founder, they’re being sued, somebody copied their idea, nothing’s working, the company’s sideways, they got hacked. It is a shit show most days. You have to have a certain desire to deal with insurmountable odds. You’ve got to have a little Han Solo in you, not C-3PO.”

Emotionally handling that the chaos that is an inevitable part of an Angel investor’s life is not an easy thing. When startups and businesses in a portfolio fail they are people you know. It can be both a grind and a struggle to do this work but it seems to be something that Calacanis is well suited for. Fred Wilson writes:

“In poker folding is simple.  In the VC business, it’s not that simple.  Sometimes you can fold by selling the company or the assets.  Other times, you need to shut the business down.  It’s not easy and many inexperienced VCs make the mistake of playing the hand out because they don’t want to face the pain of folding.  That’s a bad move.”

  1. “[Angel investing] is sort of like playing really bad cards with a very deep stack and seeing a lot cheap flops.” “As an angel you have to be able to focus on the 5% chance that things will go really, really well. As a VC you have to look at the downside a lot more because you make 1/20th the number of bets. I can put $25k into 30 companies a year and if I hit one big winner every 10 years I’m golden. VC doesn’t exactly work like that… you might do 20 investments over 10 years — if you were going fast!”  “There are probably 10,000 projects angel funded in technology per year (say 5x the number of venture deals per year, which I understand is around 2,000 here in the USA). If there are 10 angels in each deal (another guesstimate), that means 100,000 angel investments get put into this bucket per year. Over 10 years we have 1,000,000 swings at bat by angels. If we have 40 unicorns every 10 years here in the USA there are 400 angel lottery tickets (40 unicorns with 10 angels each) in the 1,000,000 lottery tickets issued. By this absurdly incorrect math, you would have  .04% chance of getting a lottery ticket: 1 in 2,500.’’ 

Marc Andreessen describes the approach of a venture capitalist as “buying a portfolio of long–dated, deeply–out-of-the-money call options.” Entrepreneurs are in the business of creating those call options and selling some of them to investors to create a pool of capital to fund the businesses. In evaluating each call option a venture capitalist is seeking a mispriced asset.  Half crazy ideas are typically more mispriced and have the convexity that venture investors need to generate grand slam financial outcomes.

There are only so many actual exits for investors. Creating a unicorn is not the same thing as getting a financial exit.


Venture backed

  1. “Angel investing is very similar to poker, where you’re playing against other people, you can increase your chances.” “The big rub in all this is that you have to get access to the unicorns as they are born.” “You can’t be ever embarrassed about hustling.”

Steven Christ writes: “The reason that you can win at poker [is that] you are not betting against the house; you are betting against the other players. This is such a crucial and fundamental difference, and it is lost on the general public. The house is not setting the odds. In roulette, there are 38 spaces on the wheel, and if you pick the correct one, the house will pay you off at 35-to-one, and they will keep the difference. The longer you play, the more you lose and the more the house wins. When the other players are setting the prices, it is an entirely different story…”

  1. “Why is there such an overlap between angel investor and poker player? It’s a couple of things. One, you’re dealing with partial information and trying to make decisions. You have to make a lot of decisions under pressure with money, exactly like investing. You’re under pressure, there’s time constraint, and you don’t have complete information. If you can have a slight edge in some way, you can outperform everybody else. It’s the same as investing. Also, deception, intimidation, reading people.”

One of the most creative thinkers ever to tackle the theory of poker was John von Neumann, a Hungarian born mathematician, physicist, inventor, computer scientist, and polymath. One biography notes that “…the inspiration for game theory was poker, a game he played occasionally and not terribly well. Von Neumann realized that poker was not guided by probability theory alone, as an unfortunate player who would use only probability theory would find out. Von Neumann wanted to formalize the idea of ‘bluffing,’ a strategy that is meant to deceive the other players and hide information from them.” The Financial Times elaborates:

“John von Neumann believed that if you wanted a theory that could explain life, you should start with a theory that could explain poker – game theory. “Real life consists of bluffing, of little tactics of deception, of asking yourself what is the other man going to think I mean to do, and that is what games are about in my theory.” High quality global journalism requires investment. It was the bluff that interested von Neumann. Novices wrongly believe that bluffing is merely a way to win pots with bad cards. In the 1972 final of the World Series, the famous hustler Amarillo Slim won because he had bluffed so often that when he finally put all his chips in the pot with a full house (a very strong hand), his opponent assumed Slim was bluffing again; called (matching the bet), and lost. A player who never bluffs will never win a big pot, because on the rare occasions that he raises the betting, everyone else will fold before committing much money. Then there’s the reverse bluff: acting weak when you are strong. In the 1988 World Series, the Chinese-born Johnny Chan (dubbed the “Orient Express” because he won money so quickly) passed up every opportunity to raise the stakes and meekly called his opponent’s bets. By the last round of betting, his opponent became convinced that Chan didn’t have a hand and bet everything he had. Chan called and turned over a straight – a strong hand – scooping up $700,000 and the title of world champion.”

  1. “I know I’m not smarter than Google. Me vs. a Google person playing chess I’d lose. Me vs. anybody at Google in poker, I’m rich; I will win. You have to know what game you’re playing. I would not play chess vs. anybody at Google or write an algorithm.”

One of the best ways to improve your poker results is to play against weak competition and to avoiding being the weak competition. This is essentially the circle of competence principle put to work in poker. The Poker Dictionary defines a few key terms relevant to circle of competence: “In the 1990s the bad players were referred to as fish. Nowadays they are called donkeys. A tournament that is full of donkeys or bad players is called a donkament.” Having some fish or donkeys in a card game wakes winning easier. Amarillo Slim said once: “No river, no fish.” A similar saying is: “You lead a horse to water, but a donkey will follow you all the way to the river.” Some people believe that a donkey is a bit different than a fish because fish are just prey and a donkey can have dumb luck and take your money.

  1. “Angel investing is gambling in the same way poker is: it involves a lot of skill and discipline on top of the luck.” 

In all questions that involve the relationship between investing and games the “go to” expert is Michael Mauboussin:

“Luck plays a huge role in determining results in investing, especially in the short term. Luck is also prominent in business strategy and card games —including blackjack and poker. One way to think about the difference between the results for pianists and poker players is to visualize a continuum with all luck at one end and all skill at the other. Then place activities along that continuum. Roulette wheels and lotteries are on the luck side, and swim and crew races are on the skill side. Most of the action in life sits between those extremes…. there’s no way to know for sure how Phil Ivey will fare in the next World Series of Poker because even if he plays his cards just right, he may suffer from awful luck.”


  1. “If you’re at the poker table and you can’t tell who you’re better than and who the fish is, you’re the fish. That’s, inevitably, how everybody starts. What you have to do is try to slowly move yourself up.” 

An academic paper that looks at poker makes a point about poker that is a lot fancier but less informative.

“The results show that competitive edges attenuate as one moves up levels, and tight-aggressive strategies––which tend to be the most remunerative––become more prevalent. Further, payoffs for different combinations of cards, varies between levels, showing how strategic payoffs are derived from competitive interactions. Smaller-stakes players also have more difficulty appropriately weighting incentive structures with frequent small gains and occasional large losses. Consequently, the relationship between winning a large proportion of hands and profitability is negative, and is strongest in small-stakes games.”

  1. “It’s a portfolio strategy. If 7 out of 10 fail, 8 out of 10 fail, what you’re trying to do is figure out what those 2 out of 3. Let’s say 2 or 3 out of 10 don’t fail. You want to quickly figure out who those 2 out of 3 are, and then take your 25k investment and make a 100k investment in those 3. Then you figure out, let’s say you’ve done 100, and you have 4 of them that are really breaking out, you want to figure out which those 4 are, so you can put 250k into those. On a name basis, 7 out of 10 of your investments fail. Say you put 10k into each, that’s 70k gone. Then the last 3, let’s say you put 100k in each. Now, you have 300 active, and you put 100 into the first 10. 7 failed, so you have 330k of your 400k is still in play. You see what I did there? You do 10k in 10, 70 goes away, 30,000 is still active. You put 100k in each, now you’ve got 330k still active. Then, 2 of those sell off and you get your money back, fine, you’ve got 110 back. Great, you have 220 back of your 400 committed. Then, you put half a million into that one this really breaking out, and that half a million goes 20, 30, 50x. Holy shit, now you’ve got a $10 million or $25 million return on your hand, and you’ve played the game properly. You’re doubling down, and then you’re going all-in. It is just like poker. When you get pocket aces, or ace, king, or 10, jack suit, or whatever it is, you make an exploratory bet. When the flop comes and your 10, jack is met with ace, king, queen, you’re like, ‘Oh my God, these donkeys probably have ace, queen and ace, king. They’re going to be batting like maniacs, and I have the stone cold nuts right now.’” 

Fred Wilson writes about one important idea that Calacanis is talking about in this way: 

“If you structure your deals appropriately, you can often get three or four rounds.  As your hand strengthens, the cards get better, you increase the betting, putting more money at risk in each subsequent round.  That’s how smart poker players win and it’s also how smart VCs win. The poker analogy only works so far.  Bluffing doesn’t work in the VC business.  If you’ve got a band hand, you really can’t bluff your way out of it.  But on the other hand, you can impact the cards you’ve got.  You can work with management, beef it up, switch markets, buy some businesses, etc.  You can significantly improve your hand if you work at it, something that’s not really possible in poker.”

In a book entitled Venture Investing in Science Douglas Jamison and Stephen Waite argue:


“What the heck are ‘the nuts’?” you might ask if you are not a poker player.  The origin story for that term goes like this:

“This poker term dates way back to the Wild West where cowboys would gather round a table, preferably in a saloon but alternatively around a campfire, and play cards. Back then poker players would not always bet with cash or chips. It was a more rustic time, and men would often bet their horse and wagon on a poker hand. Legend has it that when a cowboy bet his wagon he would unscrew the nuts from his wagon wheels and place them in the pot. The reason behind this gesture was that in the event that he lost the pot he could not leap up, hop into his wagon and ride away with his wager. The fact that he was willing to put those nuts in the pot as surety for the strength of his hand resonated through the prairie, and came to be synonymous with the best hand. A cowboy would only bet “the nuts” when he was convinced that his hand was the best out there.”

Bankroll management is an important part of Angel investing and poker. I wrote about this set of issues in my post on Ed Thorp. He is how one poker player manages his bankroll:

  1. “Poker, like entrepreneurship,  is very painful when you start, but then you get better at it.” 

Investing, poker and business are skills that you can get better at. Skill matters in poker and venture capital. Freakonomics author Steven Levitt with Thomas Miles did a study and concluded:

“…we analyze that question by examining the performance in the 2010 World Series of Poker of a group of poker players identified as being highly skilled prior to the start of the events. Those players identified a priori as being highly skilled achieved an average return on investment of over 30 percent, compared to a -15 percent for all other players. This large gap in returns is strong evidence in support of the idea that poker is a game of skill.”

Douglas Jamison and Stephen Waite argue:


  1. “Poker has a lot of things that entrepreneurship is about. Trying to figure out a situation with limited information.” “[Investing and poker] are very analogous and I think reading people is a skill of angel investors.  Reading people understanding people. Understanding motivation and then also trying to solve problems with limited information. When you look at poker you’re trying to uncover this riddle and you don’t have complete information.”  “Jason’s Law of Angel Investing” states: “You don’t need to know if the idea will succeed — just the person.” “Jason’s Second Law of Angel Investing” states: “Your success is correlated to the amount of time you give to founders.” “I have a theory about angel investing, which is basically you’re investing in the person and that the more outlandish the idea is, and the less people understand it, the greater the chances you should invest in it are.” “People who are crafts persons and who have craftsmanship in their work, they will always happen, whether in the early stage or late stage. When I see a particularly well-designed product, or somebody understands their metrics, I know that person cares. People are in this wacky belief system that their idea matters, when it does not. All that matters is what you build.”

This last item is obviously grab bag of quotes from Calacanis. In this collection of quotes you see his investing thesis come more into the light. These are a good way to end this post since it is getting a bit long. Calacanis proves that great investors hustle, have an extensive scuttlebutt network and read constantly.


Angel: How to Invest in Technology Startups-Timeless Advice from an Angel Investor Who Turned $100,000 into $100,000,000 https://www.amazon.com/Angel-Invest-Technology-Startups-Timeless-Investor/dp/0062560700


















A Dozen Lessons about Business and Investing from Poker


You can’t write about the relationship between games and investing without quoting Michael Mauboussin. I will do so often in this post. He is the master. Read his books. All of them. Then read them again.

Set out below are the usual dozen lessons you can learn from poker:

  1. “Poker is a game where you don’t have to have the best hand to win. Poker is really reading other people and reading human emotion, which certainly comes into play in business.” Charlie Ergen 

One of the stories people tell about Charlie Ergen is how he was a blackjack card counter before he created the DISH satellite television business. One part of the lore about his poker playing is this anecdote:

“In 1980, a few months before Charlie Ergen co-founded the company that would become Dish Network, he and a gambling buddy strode into a Lake Tahoe casino with the intention of winning a fortune by counting cards. Ergen, then 27, had bought a book called Playing Blackjack as a Business and studied the cheat sheets. Unfortunately for him, a security guard caught his pal lip-syncing numbers as the cards were dealt. The two were kicked out and subsequently banned from the casino.”

Ergen knows the smartest business people and investors don’t really “gamble” (a net present value negative activity) since their intent is to bet only when the odds are substantially in their favor (i.e., a net present value activity). Ergen understands this distinction since he has the same outlook as Steve Crist of the Daily Racing form:

“A good litmus test for someone being a liar and an idiot is if someone ever tells you, ‘I am really good at roulette,’ or ‘I win at craps,” or ‘I have a system for beating the slot machines.’ There is no such thing. These are games with fixed percentages. The casino might as well attach a leach to your forehead when you walk in the door because the longer you stay, the more you will lose, except for short-term, meaningless fluctuations. The exceptions to [the previous] rule are blackjack and poker. If you count cards diligently in blackjack, you can get a 1.5 percent edge over the house. Casinos, of course, don’t get built by players having edges, so the casinos will eject you if they figure out that you’re counting cards.”

The best example of what essentially was poker playing I have even seen in business is how Bill Gates managed Microsoft’s relationship with IBM and took them to the cleaners. Gates said in 1993:

“We would have been glad at sometime to sell IBM part of the company. We even proposed to IBM that they buy part of Microsoft– I think it was 30%– and they turned us down. At every stage of our relationship, they had project groups doing work to wipe us out. We stayed ahead, but it wasn’t simple.” Computerworld, May 24

This story has never been properly told.  If someone does write an accurate account someday, it will convey poker playing skills at the highest level. The relationship wasn’t just a dumb lumbering IBM not understanding software (although there were elements of that). IBM was actively engaged in a campaign to “wipe out” Microsoft. Gates played hand after hand against IBM in this business poker game and won every time. The OS/2 era alone is worthy of an entire master class in business strategy.

2. “If there weren’t luck involved, I would win every time.” Phil Hellmuth

There is no substitute for a sound process in an activity like investing. When playing poker you can make a wise decision and still lose or make a terrible decision and still win. As Michael Mauboussin writes: “If you compete in a field where luck plays a role, you should focus more on the process of how you make decisions and rely less on the short-term outcomes. The reason is that luck breaks the direct link between skill and results—you can be skillful and have a poor outcome and unskillful and have a good outcome. A good process can lead to a bad outcome in the real world, just as a bad process can lead to a good outcome. In other words, both good and bad luck can play a part in investing results. But the best investors and business people understand that over time a sound process will outperform.” Over a shorter period  of time, luck can fool you into believing that someone has skill or good judgement. On this point I have always liked this 1993 quote from Bill Gates on luck: “The notion that people who have been lucky enough to make a lot of money know something or are worth listening to is a risky proposition.” Chicago Tribune, October 24.

Luck of course is at the root of what poker players calls a bad beat. There are many stories one of them is:


3. “On any given day a good investor or a good poker player can lose money.” David Einhorn 

Mauboussin tells this story about poker:Jim Rutt, who used to be the CEO of Network Solutions. He talked about playing poker when he was a young man.By day, he would learn about the different probabilities, and look for poker tells and pot odds, and all this stuff, and by night he would play. He played in progressively tougher games, and won some, lost a little. Eventually, his uncle pulled him aside and said, “Jim, it’s time to be less worried about getting better, and more worried about finding easy games.”

Mauboussin tells another story to illustrates this point:

“[A baseball executive] was in Las Vegas sitting next to a guy who has got a 17. So the dealer is asking for hits and everybody knows the standard in blackjack is that you sit on a 17. The guy asked for a hit. The dealer flips over 4, makes the man’s hand, right, and the dealer sort of smiles and says, “Nice hit, sir?”  Well, you’re thinking nice hit if you’re the casino, because if that guy does that a hundred times, obviously the casino is going to take it the bulk of the time. But in that one particular instance: bad process, good outcome. If the process is the key thing that you focus on, and if you do it properly, over time the outcomes will ultimately take care of themselves. In the short run, however, randomness just takes over, and even a good process may lead to bad outcomes. And if that’s the case: You pick yourself up. You dust yourself off. You make sure you have capital to trade the next day, and you go back at it.”

  1. “Ain’t only three things to gambling: knowing the 60-40 end of the proposition, money management, and knowing yourself. Any donkey knows that.”  Puggy Pearson

This statement from Puggy Pearson is one of the favorite quotes of Michael Mauboussin who wrote one of his many essays specifically on Pearson.” In that essay Mauboussin explain’s what Pearsin means:

“Pearson’s message may be colloquial, but that in no way undermines its power. We can express the ideas more formally, and readily draw out critical investment concepts. Taken together, Pearson’s points indeed provide a strong foundation for investment success. The core of Pearson’s point is that investors should seek financial opportunities that have a positive expected value. A positive expected value opportunity has an anticipated benefit that exceeds the cost, including the opportunity cost of capital. Not all such financial opportunities deliver positive returns, but, over time, a portfolio of them will. So how should investors seek such opportunities? First off, investors must understand their source of competitive advantage. Markets reflect the collective expectations of investors, and embody more information than any individual can hope to have. An investor with a competitive advantage knows something that the market doesn’t—based either on superior information or on superior analysis of known information. An investment is attractive if it trades below its expected value. Expected value, in turn, is a function of potential value outcomes and the probability of each outcome coming to pass. Investing is fundamentally a probabilistic exercise, and leading investors always think in probability terms. In Pearson’s words: ‘I believe in logics. Cut and dried. Two and two ain’t nothing in this world but four. But them suckers always think it’s somethin’ different. I play percentages in everything.’ Investing is the constant search for asymmetric payoffs, where the upside opportunity exceeds the downside risk. Ben Graham described margin of safety as buying an investment for less than what it is worth. The larger the discount, the greater the margin of safety. That’s knowing the 60-40 end of a proposition.”

My blog post last weekend on Ed Thorp has loads of great material on the Kelly criterion. I win’t repeat that here other than to repeat two sentences from Thorp which make the key points: “If you bet too much you’re likely to be wiped out. If you bet too little it takes forever to make any money, so there’s a happy medium.”

  1. “Coming out ahead at poker requires that I win a lot on my winning hands and lose less on my losers. But insisting that I’ll never play anything but ‘the nuts’ – the hand that can’t possibly be beat – will keep me from playing lots of hands that have a good chance to win but aren’t sure things.  For a real-life example, Oaktree has always emphasized default avoidance as the route to outperformance in high yield bonds. Thus our default rate has consistently averaged just 1/3 of the universe default rate, and our risk-adjusted return has beaten the indices. But if we had insisted on – and designed compensation to demand – zero defaults, I’m sure we would have been too risk averse and our performance wouldn’t have been as good. As my partner Sheldon Stone puts it, ‘If you don’t have any defaults, you’re taking too little risk.’” Howard Marks

My blog posts on Howard Marks are here and here.  In his book Margin of Safety, Seth Klarman writes:

“Most investors strive fruitlessly for certainty and precision, avoiding situations in which information is difficult to obtain. Yet high uncertainty is frequently accompanied by low prices. By the time the uncertainty is resolved, prices are likely to have risen. Investors frequently benefit from making investment decisions with less than perfect knowledge and are well rewarded for bearing the risk of uncertainty. The time other investors spend delving into the last unanswered detail may cost them the chance to buy in at prices so low that they offer a margin of safety despite the incomplete information.” 

Sometimes the right result is found through trial an error. At other times intelligence and observation are the key factors. There is also luck involved of course and a keen understanding of human nature. In their famous book In Search of Excellence Tom Peters and Bob Waterman write:

“There is a quality in experimentation as a corporate mind set that resembles nothing so much as a game of stud poker. With each card, the stakes get higher and with each card, you know more, but you never really know enough until the last card has been played. The most important ability in the game is knowing when to fold.”

As an example of business people making big bets, here are Bill Gates and Steve Jobs talking about a big bet made by Apple and a simultaneous big bet by Microsoft:

“Bill: One of the most fun things we did was the Macintosh and that was so risky. People may not remember that Apple really bet the company. Lisa hadn’t done that well, and some people were saying that general approach wasn’t good, but the team that Steve built even within the company to pursue that, even some days it felt a little ahead of its time–I don’t know if you remember that Twiggy disk drive and…

Steve: 128K.

Bill: The team that was assembled there to do the Macintosh was a very committed team. And there was an equivalent team on our side that just got totally focused on this activity. Jeff Harbers, a lot of incredible people. And we had really bet our future on the Macintosh being successful, and then, hopefully, graphics interfaces in general being successful, but first and foremost, the thing that would popularize that being the Macintosh….We made this bet that the paradigm shift would be graphics interface and, in particular, that the Macintosh would make that happen with 128K of memory, 22K of which was for the screen buffer, 14K was for the operating system.

Steve: What’s interesting, what’s hard to remember now is that Microsoft wasn’t in the applications business then. They took a big bet on the Mac because this is how they got into the apps business. Lotus dominated the apps business on the PC back then.”

  1. “It’s very important for most people to know when not to make a bet, because if you’re going to come to the poker table, you’re going to have to beat me, and you’re going to have to beat those who take money. So, the nature of investing is that a very small percentage of the people take money, essentially, in that poker game, away from other people who don’t know when prices go up whether that means it’s a good investment or if it’s a more expensive investment.” Ray Dalio

Many people agree with these points made by Dalio, including these three famously successful people:

Warren Buffett: “The important thing is to keep playing, to play against weak opponents and to play for big stakes.” “If you’ve been playing poker for half an hour and you still don’t know who the patsy is, you’re the patsy.”

Charlie Munger: “For a security to be mispriced, someone else must be a damn fool. It may be bad for the world, but not bad for Berkshire.” Charlie Munger was once asked who he was most thankful for in all his life. He answered that he was as most thankful for his wife Nancy’s previous husband.  When asked why this was true he said:  “Because he was a drunk. You need to make sure the competition is weak.”

Tony Hseih of Zappos: “An experienced player can make ten times as much money sitting at a table with nine mediocre players who are tired and have a lot of chips compared with sitting at a table with nine really good players who are focused and don’t have that many chips in front of them. In business, one of the most important decisions for an entrepreneur or a CEO to make is what business to be in. It doesn’t matter how flawlessly a business is executed if it’s the wrong business or if it’s in too small a market.”

  1. “One of the best antidotes to this folly is a good poker skill learned young. The teaching value of poker demonstrates that not all effective teaching occurs on a standard academic path.” “Part of what you must learn is how to handle mistakes and new facts that change the odds. Life, in part, is like a poker game, wherein you have to learn to quit sometimes when holding a much loved hand.” “Playing poker in the Army and as a young lawyer honed my business skills. What you have to learn is to fold early when the odds are against you, or if you have a big edge, back it heavily because you don’t get a big edge often. Opportunity comes, but it doesn’t come often, so seize it when it does come.” “And the wise ones bet heavily when the world offers them that opportunity. They bet big when they have the odds. And the rest of the time they don’t. It’s just that simple.” Charlie Munger 

A simple point Munger makes again and again is that understanding probability and statistics is essential in both card playing and investing. Munger bets big when he sees a situation that is “net present value positive” over time after fees and expenses. Bets that are net present value negative are avoided. Amarillo Slim has a view that is similar to Munger: “I like to bet on anything—as long as the odds are in my favor….there are people who love action and others who love money. The first group is called suckers, and the second is called professional gamblers, and it was a cinch which one I wanted to be.” Here’s a story about Slim putting that principle to work:

“Bobby Riggs, the 1939 Wimbledon Tennis Champion tried to hustle Amarillo Slim in Ping Pong. Riggs was looking to bust Slim’s skinny ass. Slim tells the story, “I told Riggs I would play him in Ping Pong straight up with one stipulation: that I got to choose the paddles. “We both use the same paddle?” Bobby asked. “Yessir.” “So when you show up with two of the same paddles, can I get my choice of which one of them?” “Yessir, so long as I can bring the paddles.” Bobby thought I was pulling a schoolboy’s scam—that it was a weight thing or that one of the paddles was hollow or something. But once I told him that he could choose whichever of the two paddles he wanted to use, he couldn’t post his money fast enough. We bet $10,000 and agreed to play at two o’clock the next day. Before I left, just to avoid any misunderstanding, I confirmed the bet: We were to play a game of Ping Pong to twenty-one, each using the paddles of my choosing. I showed up the next day at the Bel Air Country Club ready to wage battle. When Bobby asked to see the paddles, I reached into my satchel and handed him two skillets, the exact same weight and size, and told him he could use either one. Now, Bobby was about as coordinated an athlete that ever lived, but he was swinging that skillet like a fry cook on speed. It wasn’t until I had him buried that he started to get the hand of that skillet, but it wasn’t soon enough. I won the game 21-8, and it could have been much worse. Once again I proved that you can make a living beating a champion just by using your head instead of your ass. The easiest person in the world to hustle is a hustler, and Bobby had taken the bait like a country hog after town slop. You see, I had been practicing with that skillet since I saw him in Houston.”

  1. “Poker is a lot like sex, everyone thinks they are the best, but most people don’t have a clue what they are doing.” Dutch Boyd

Overconfidence is one of many behavioral biases that can trip up a poker player or investor. Charlie Munger likes to use this example to explain this bias: “A careful survey in Sweden showed that 90 percent of automobile drivers considered themselves above average. And people who are successfully selling something, as investment counselors do, make Swedish drivers sound like depressives.” Munger is talking about investing here but he may as well have been writing about poker: “The primary problem with this bias is that people who should be buying index funds think they can be successful active investors. Munger has said: “Most people who try don’t do well at it. But the trouble is that if even 90 percent are no good, everyone looks around and says, ‘I’m the 10 percent.’”

  1. “In poker, a player collects different pieces of information—who’s betting boldly, what cards are showing, what this guy’s pattern of betting and bluffing is—and then crunches all that data together to devise a plan for his own hand.” Bill Gates

When Bill Gates was a student at Harvard people he went to school with quickly found out how hard he works to learn and how persistent he can be:

“He took up poker with a vengeance. The games would last all night in one of the common rooms of Currier House, which became known as the Poker Room. His game of choice was Seven Card Stud, high low. A thousand dollars or more could be won or lost per night. Gates was better at assessing the cards than in reading the thoughts of his fellow players. “Bill had a monomaniacal quality,” Braiterman said. “He would focus on something and really stick with it.” At one point he gave Paul Allen his checkbook to try to stop himself from squandering more money, but he soon demanded it back. “He was getting some costly lessons in bluffing,” said Allen. “He’d win $300 one night and lose $600 the next. As Bill dropped thousands that fall, he kept telling me, ‘I’m getting better.’ ” He was known to be an aggressive player,” says C. Greg Nelson ‘75. “But in the crowd at Currier House where we played, he was about the median—definitely not in the top quartile.” According to Nelson, the group usually played with six people and allowed participants to buy into the game for $100. As the year went on, the pot would grow until some hands were being played for over $1,000.”

Gates is also very practical. When the Altair computer came out Gates “decided that I better buy one.  I thought it was a better use of my money than losing at poker.” The process did have some significant befits according to Steve Ballmer who has said that Microsoft’s success in business was “basically an extension of the all-night poker games Bill and I used to play back at Harvard. Sometimes whole divisions would get moved just because someone bet two pairs against an inside straight.  People were always wondering why [co-president] Jim Allchin ended up with so much power. What can I say? He bet big and won big.”

The pattern recognition and bluffing part of poker is fascinating. Tom Schneider, a four-time World Series of Poker bracelet winner once said:

“I pick up clues immediately. If you come in, and all your bills are 20s, it means you don’t have casino chips and you don’t have 100s. It means you went to the bank, and money is probably more important to you. You’ll be a little tighter with it than somebody who comes in with $20,000 in $5,000 casino chips, which means they’re probably a gambler in the pit and money won’t mean as much to them.”

But poker requires skills that transcend simply knowing the odds of completing any particular hand. It requires a split-screen ability to read the other people at the table while maintaining an awareness of how they are reading you. It requires what is called “leveling”: the ability to move fluidly and accurately in one’s imagination from the hands that all the other players are representing, to the hands that they probably have, to the hand that they think you have, to the hand that they think that you think that they think you have. The acute awareness and processing ability required to quickly go through a complex checklist and get it right—while controlling your thoughts and behavior so that others can’t read you with any equivalent degree of accuracy—is what separates poker pros from casino operators and other crude types who profit from the fact that large numbers of people are dumb or drunk and can’t do math.”

The number of possible “tells” that can potentially be exploited in poker is gigantic:

“Because poker is a game of human interaction, we sometimes receive clues from other players, based on changes in their betting patterns or their physical demeanor, which indicates the strength or weakness of their hand. These are called “poker tells.” A player gains an advantage if he observes and understands the meaning of another player’s tell, particularly if the poker tell is unconscious and reliable. Sometimes a player may even fake a tell, hoping to induce his opponents to make poor judgments in response to the false poker tell. After all, poker is a game of deception. Poker tells come in two forms: (1) Betting patterns and (2) Physical tells.”

  1. “Nobody is always a winner, and anybody who says he is, is either a liar or doesn’t play poker.” “The over-under, is just another example of how the bookmakers are always looking for more options to give the guesser an opportunity.”  Amarillo Slim

Charlie Munger’s best essay and arguably the one that made him most famous is entitled:  “A Lesson on Elementary, Worldly Wisdom as It Relates to Investment Management and Business” and it can be found here.  In this wonderful essay is a long passage which includes this language:

“The model I like—to sort of simplify the notion of what goes on in a market for common stocks—is the pari-mutuel system at the racetrack… Everybody goes there and bets and the odds change based on what’s bet.  That’s what happens in the stock market. Any damn fool can see that a horse carrying a light weight with a wonderful win rate and a good post position etc., etc. is way more likely to win than a horse with a terrible record and extra weight and so on and so on.  But if you look at the odds, the bad horse pays 100 to 1, whereas the good horse pays 3 to 2. Then it’s not clear which is statistically the best bet using the mathematics of Fermat and Pascal….”

My essay on Steve Crist discusses the meaning of this point so I won’t repeat that here.

  1. “If you don’t study any companies, you have the same success buying stocks as you do in a poker game if you bet without looking at your cards.” Peter Lynch

If you are going to win at poker you need to have an edge of some kind. That means doing things like acquiring skill and finding better information.  Howard Marks writes: “The investor’s time is better spent trying to gain a knowledge advantage regarding ‘the knowable’: industries, companies and securities. The more micro your focus, the great the likelihood you can learn things others don’t.” In addition to having an informational edge, outlook is important. Poker professional Doyle Brunson once said: “Poker is not a game where the meek shall inherit the earth.” If you don’t do the work, understand probability, manage your bankroll well, manage your emotions and understand the emotions of others, you are going to get your clock cleaned in poker and in business.

Somtimes the best way to learn the importance of something is to go without it as an experiment. This link tells a story about a famous player winning without looking at their cards:

  1. “This fricking donkey stuffs $15,000 in with king-jack. I mean, the guy can’t even spell poker.”  Phil Hellmuth

Humans love stories and part of the fun of playing poker is the ability of a player to tell a story like Hellmuth just did. Business for me is the same way. Part of the fun of this blog is telling stories. A great story told well is one of the best ways ever invented to teach people about a topic. Before the invention of written language stories were the only way that culture and history were conveyed from generation to generation. As an example, I edited two books of stories collected by my Great Grandfather Judge Arthur Griffin that he used to help establish native American treaty rights since there was no other written record that they could use to make their case. The best business people and founders are great story tellers. Some of the best story tellers like Mark Twain were also poker fans as was the great sportswriter Grantland Rice. Twain once said: “There are few things that are so unpardonably neglected in our country as poker. Rice said it better: “It’s not whether you won or lost, but how many bad-beat stories you were able to tell.

Maybe the best way to end this post is with a Puggy Pearson story. It is sort of long (about six minutes) and you will probably enjoy it most if you are a poker player:


Bill Gates at Harvard: http://news.harvard.edu/gazette/story/2013/09/dawn-of-a-revolution/

Charlie Ergen: http://www.hollywoodreporter.com/news/dish-networks-charlie-ergen-is-432288

Mauboussin on Puggy Pearson: https://www.scribd.com/document/112879396/Puggy-Pearson-s-Prescription

My Steven Crist post https://25iq.com/2016/05/21/a-dozen-things-ive-learned-from-steven-crist-about-investing-and-handicapping-horses/

Einhorn http://www.thinkingpoker.net/

Mauboussin:    https://research-doc.credit-suisse.com/docView?language=ENG&format=PDF&sourceid=em&document_id=x745112&serialid=knrGGNw%2Bo620toTTx96qBQ%3D%3D

Poker tells:





A Dozen Lessons on Investing from Ed Thorp

“Edward O Thorp is the author of Beat the Dealer, which was the first book to prove mathematically that blackjack could be beaten by card counting, and Beat the Market, which showed how warrant option markets could be priced and beaten. He also was the co-inventor of the first wearable computer along with Claude Shannon. Thorp also pioneered the use of quantitative investment techniques in the financial markets (Option Arbitrage, Warrant Modeling, Convertible Arbitrage, Index Arbitrage and Statistical Arbitrage).”  

Thorp speaks clearly and from the heart. He reminds me of that other ultra rational decision maker Charlie Munger. Despite his prodigious intellectual gifts Thorp remains grounded and approachable. A few sentences reveals his gift for communication which reminds me of Michael Mauboussin:

“My life has been an adventurous journey I thought readers would enjoy my stories of the people I met and the challenges I faced.” “Chance can be thought of as the cards you are dealt in life. Choice is how you play them.” “A lot of big choices that you make at some point or other, and then there are things that you can’t control like who your parents were, and what kind of economic circumstances you were brought up in, where you started. Did you start 20 yards behind the start line or 20 yards ahead of it, or right on it? People start in different places. Those are cards that are dealt.”

Set out below are usual twelve lessons I have learned from Thorp:

  1. “Try to figure out what your skill set is and apply that to the markets. If you are really good at accounting, you might be good as a value investor. If you are strong in computers and math, you might do best with a quantitative approach.” “If you aren’t going to be a professional investor, just index.”

Thorp likes to stay within his circle of competence. This is a hallmark of people who are rational. In that sense, Thorp reminds me of Warren Buffett. But unlike Buffett, Thorp did not make his fortune in the market by analyzing businesses and instead found his special competency in statistical arbitrage, which he more or less invented. Thorp was able to successfully take his considerable mathematical and intellectual gifts and apply them in an area where he has a significant advantage.

  1. “The way I sized up the Ben Graham approach was that it would be a total lifetime of effort. It was all I would be doing. Warren demonstrated that. He’s the champion of champions. But if I could go back and trade places with Warren, would I do it? No. I didn’t find visiting companies something I wanted to do. I never even thought about finance until I was 32.”

Thorp also decided early in life to get in the side car of other people who have a different competitive advantage. He invested in Berkshire when the stock was trading at $982 and still hold those shares today. When Buffett was winding up his partnership he was asked to do some due diligence on Thorp as an investor by a mutual friend. That chain of events resulted in Thorp and his wife playing bridge with Buffett in 1968. Thorp described the meeting: “The Gerards invited my wife Vivian and I to dinner with Warren and his charming blonde wife Susie.  Impressed by Warren’s mind and his methods, as well as how far he’d already come, I told Vivian that he would eventually become the richest man in America.  A mutual friend talked recently with Warren, who spoke warmly of our meetings, of Beat the Dealer and Beat the Market, and of non-transitive dice.”

Speaking of impressive mental calculation, Barry Ritholz recently interviewed Thorp and watched him calculate his return on his Berkshire shares in his head. Thorp is the sort of person who taught himself FORTRAN so he would create his card counting techniques for Blackjack on an IBM 704 mainframe. The number of things Thorp taught himself is astounding.

It is a good thing to remember that you are not Ed Thorp, Warren Buffett or Charlie Munger and neither and I. If you have similar mathematical gifts as Ed Thorp or Buffett, good for you. I do not have them. Even if you have those mathematical gifts, are you are rational as Thorp? Do you have control of your ego sufficiently to stay within your circle of competence?

  1. “The first group of investors are those who do not want to do a lot of work who should invest in indexes. Index investors do better than maybe 90% of all other investors who are busy paying fees to advisers.” “The second group are those who would like to learn more about securities. They are entertained by following and analyzing securities. I think they can learn about special, unusual things although there is a price for that education. [They are] interested in the market, and it’s kind of fun for them. Those people if they want to learn more should go out and have their go at trying to make some money, but they shouldn’t use the bulk of their resources to do this. If they find something that really works then they can start putting more money into it. They’ll find that most of the time they haven’t really found anything that really works.” “The third group, which are the professional people some of whom actually get an edge. Most of whom don’t, but some of whom do. Those people get a start somehow in the market just like I got a start with an option’s formula, so I have an edge. I get in. I build an organization, which is small, and it gradually grows. It gets more and more skills. It gets into more and more kinds of investing. You, basically, get over the hurdle and get yourself established. If you can do that as a professional then you’re kind of on your way to collecting what people call Alpha, excess return. Then there’s the fourth group, which I don’t have much interest in, and those are the ones who are simply asset gatherers. They’re in there to collect fees and get rich, but there’s nothing really very interesting in what they do.” 

In which category do you fit? Do you enjoy learning a lot about businesses? Are you willing to devote many hours a day to researching businesses? Have you tried picking stocks with a small portion of your assets and carefully tracked results to see if you are any good at it?

  1. “[Slot machines are] the most moronic devices ever, one of the stupidest activities of humankind. People play negative-expectation games. That’s something I’m not willing to do. I’ve never even bought a lottery ticket.” “The first thing people who have control do is tilt the playing field. Maybe the majority of wealth is accumulated because of tilted playing fields. Not because of merit.” “In standard gambling games in casinos you can generally calculate what the casino’s edge is, or if you figure out how to count cards you can calculate what your edge over the casino is. It’s a fact, a mathematical fact, that if you play a game like this and the casino has the edge it will eventually collect all your money if you play long enough. On the other hand, if you have an edge your bankroll will grow and grow and grow. Basically, what happens is your bankroll either grows or shrinks depending on what your edge is or what your disadvantage is. There’s luck that pushes it up and down around that growth curve. That’s the way things look in the gambling world.”

If you look carefully at what Thorp has accomplished with his funds he was not gambling if you define it as a “negative net present value” activity (which you should). Thorp only invested when he had a statically generated advantage or as he calls it “an edge.” I have never bought a lottery ticket either. I would rather drop a large rock on my toe than gamble.

  1. “The overlap of interest between gambling and the stock market is very high. There are so many similarities and so much one can teach you about the other. Actually, gambling can teach you more about the stock market than the other way around. Gambling provides an analytically simpler world, and you can see principles and test theories.” “I chose to investigate blackjack.” “I was lucky in that I came at investments through blackjack tables. And the blackjack tables are an amazingly good training ground for learning how to invest, how to think about investments, how to manage them. And the reason is that they teach you, on the one hand, to use probability and statistics to evaluate things. And on the other, they teach you discipline. When you find something, you stick to it. “Most of the games, whatever happens on one trial or one play of the game doesn’t have any influence on what’s going to happen next. I realized that in a minute or two that if cards were used up during the play of the game, the odds would shift back and forth – sometimes for the casino, sometimes for me.” “Say a blackjack player is dealt a ten and a six, while the dealer’s showing a ten. You can calculate that situation, and anyone who’s played any cards knows you’re ‘supposed’ to hit. But what if your 16 is comprised of two fours and four twos? In a deck that’s ten rich, it’s a definite stand.” “Beating the blackjack tables by keeping track of the cards was, though I didn’t realize it until later, a preparation without equal for successful investing.  When I had the edge, I bet big, but not so big as to risk going broke. When the cards favored the casino, I played defense, to limit my losses. The same approach worked on Wall Street: the bigger my edge, the more I bet and the greater the risk the more cautious I was. Gambling and investing are alike – in both you risk money, which you then may win or lose.”

Again, the comparison to the methods of Charlie Munger is easy. Munger has said: “Life in part is like a poker game, wherein you have to learn to quit sometimes when holding a much loved hand….Playing poker in the Army and as a young lawyer honed my business skills … What you have to learn is to fold early when the odds are against you, or if you have a big edge, back it heavily because you don’t get a big edge often.”

  1. “One of the early things that I learned, fortunately, which was how much to bet on good situations. If you bet too much you’re likely to be wiped out. If you bet too little it takes forever to make any money, so there’s a happy medium.” “You have to make sure that you don’t over-bet. Suppose you have a 5% edge over your opponent when tossing a coin. The optimal thing to do, if you want to get rich, is to bet 5% of your wealth on each toss — but never more. If you bet much more you can be ruined, even if you have a favorable situation. It’s a formula Bell Labs scientist John Kelly devised in the 1950s for maximizing the long-term growth rate of capital. It tells you how to allocate your money among the choices available, and how much to invest as your edge increases and the risk decreases. It also avoids the over-betting that can ruin an investor who otherwise has an edge.” “There are, however, safer paths that have smaller draw downs and a lower probability of ruin. If you bet half the Kelly amount, you get about three-quarters of the return with half the volatility.  I believe that betting half Kelly is psychologically much better…. sometimes the dealer will cheat me. So the probabilities are a little different from what I calculated because there may be something else going on in the game that is outside my calculations. Now go to Wall Street. We are not able to calculate exact probabilities in the first place. In addition, there are things that are going on that are not part of one’s knowledge at the time that affect the probabilities. So you need to scale back to a certain extent because over betting is really punishing—you get both a lower growth rate and much higher variability. Therefore, something like half Kelly is probably a prudent starting point. Then you might increase from there if you are more certain about the probabilities and decrease if you are less sure about the probabilities.” “In the last 15 years or so, there has been a large flow of capital into the hedge-fund world, from $100 billion in the early 1990s to $2 trillion now. But the amount of available investing opportunities hasn’t increased that much. That has led to the over-betting phenomenon [which can result in] gambler’s ruin.” 

I remember when I first started reading about the Kelly criterion in books and essays written by Robert Hagstrom and Michael Mauboussin. It was a revelation. Imagine how cool it would have been to be a fly on the wall when Thorp and Claude Shannon were having conversations at MIT. Or learning and debating with Richard Feynman. Thorp has had such an interesting life, but the idea of he and Shannon developing the world’s first wearable computer to beat casinos at roulette is Ocean’s Eleven type stuff. In a paper detailing the shenanigans Thorp writes:

“The final operating version was tested in Shannon’s basement home lab in June of 1961.  The cigarette pack sized analog device yielded an expected gain of +44% when betting on the most favored “octant.” The Shannons and Thorps tested the computer in Las Vegas in the summer of 1961.  The predictions there were consistent with the laboratory expected gain of 44% but a minor hardware problem deferred sustained serious betting. We kept the method and the existence of the computer secret until 1966.”

Thorp was smart and rational enough to have avoided the gambler’s ruin that caught Long Term Capital Management. Elliot Turner describes a talk Thorp gave at Sante Fe Institute:

“Thorp described their strategy as the anti-Kelly.  The problem with LTCM, per Thorp, was that the LTCM crew ‘thought Kelly made no sense.’  The LTCM strategy was based on mean reversion, not capital growth, and most importantly, while Kelly was able to generate returns using no leverage, LTCM was ‘levering up substantially in order to pick up nickels in front of a bulldozer.’”

Turner also notes: “It’s been mentioned that both Warren Buffett and Charlie Munger discussed Kelly with Thorp and used it in their own investment process.”

  1. “I think inefficiencies are there for the finding, but they are fairly hard to find.” “Markets are mostly good at predicting outcomes, but very bad at anticipating black-swan events.” “When people talk about efficient markets they think it’s a property of the market, but I think that’s not the way to look at it. The market is a process that goes on, and we have depending on who we are different degrees of knowledge about different parts of that process.” 

Thorp’s track record as an investor makes a mockery of anyone who believes in the hard version of the efficient market hypothesis. Elliot Turner gives summary of Torp’s approach and results as a hedge fund manager:

“In 1974, Thorp started a hedge fund called Princeton/Newport Partners [which] used warrants and derivatives in situations where they had deviated from the underlying security’s value.  Each wager was an independent wager, and all other exposures, like betas, currencies and interest rates were hedged to market neutrality. Princeton/Newport earned 15.8% annualized over its lifetime, with a 4.3% standard deviation, while the market earned 10.1% annualized with a 17.3% standard deviation (both numbers adjusted for dividends).  The returns were great on an absolute basis, but phenomenal on a risk-adjusted basis.  Over its 230 months of operation, money was made in 227 months, and lost in only 3.” 

  1. “When the interests of the salesmen and promoters differ from those of the client, the client had better look out for himself.” 

Thorp knows that you should never ask a barber if you need a haircut. There are few things as powerful in human affairs as incentives. Both at a personal level and in society as a whole, incentives are the dominant cause of outcomes. The more you understand the impact of incentives, the more you understand life.

  1. “When there’s money and not full accountability, whether it’s in casinos or on Wall Street, there’s going to be stealing and cheating.” “My book tells how you have to be aware of cheating in both of these worlds.  At blackjack, it can be marked cards, second-dealing, or a stacked deck.  On Wall Street, it can be Ponzi schemes and other frauds, such as insider trading, fake news, or stock price manipulation. Mathematically, the biggest difference is that the odds can be figured exactly or approximately for most gambling games, whereas the numbers are usually far less certain in the securities markets.”

Munger not surprisingly agrees with Thorp: “Where you have complexity, by nature you can have fraud and mistakes. The cash register did more for human morality than the Congregational Church. It was a really powerful phenomenon to make an economic system work better, just as, in reverse, a system that can be easily defrauded ruins a civilization.One of the reasons Thorp uses a fractional Kelly approach is that it provides some protection against fraud.

  1. “Most stock-picking stories, advice and recommendations are completely worthless.” “Sell down to the sleeping point. As far as asset classes go, it is hard to know when you are in a bubble, and if you are in one, when it will pop.” “I read a good book recently, Superforecasting by Dan Gardner and Philip Tetlock. They wanted to see whether people can forecast better than chance. What they found is that experts often do not have much to tell us things of value. Experts receive a lot of media attention because they make strong, definite claims. But definitive claims are usually not accurate predictions; we can only see the future fuzzily. People that tend to weigh different possibilities can make somewhat better predictions than chance.”

The most effective way to learn this lesson is the same way you learn not to touch a hot stove as a child. But the better way is to watch someone else do it. “Just say no” to stock tips. Bernard Baruch described why stock tops are so appealing to some people in this way:

“Beware of barbers, beauticians, waiters – of anyone – bringing gifts of ‘inside’ information or ‘tips’.  The longer I operated in Wall Street the more distrustful I became of tips and ‘inside’ information of every kind. Given time, I believe that inside information can break the Bank of England or the United States Treasury.  A man with no special pipeline of information will study the economic facts of a situation and will act coldly on that basis. Give the same man inside information and he feels himself so much smarter than other people that he will disregard the most evident facts.”

  1. “People say, ‘Gee, what if your Berkshire goes down?’ I say, ‘Oh, that’s good because now I can buy more’” They say, ‘But what if it goes up?’ I say, ‘Well, that’s good too because I feel good because I feel suddenly richer.’ So let it go up or let it go down. I don’t care.”  

This statement by Thorp is a variant of a point Warren Buffett likes to make:

“This is the one thing I can never understand. To refer to a personal taste of mine, I’m going to buy hamburgers the rest of my life. When hamburgers go down in price, we sing the “Hallelujah Chorus” in the Buffett household.  When hamburgers go up, we weep. For most people, it’s the same way with everything in life they will be buying–except stocks. When stocks go down and you can get more for your money, people don’t like them anymore.”


  1. At the 2017 Daily Journal of Commerce annual meeting Charlie Munger recommended Thorp’s autobiography A Man For All Markets. Thorp tells this story about attending a Berkshire meeting in Omaha:

“Saturday night we were back at Gorat’s! The price of the T-bone dinner we had Friday was, as a “special for shareholders,” now $3 more! Charlie Munger reluctantly ‘worked’ the room we were in and I mentioned to him a tale I’d heard about his youth. Charlie had gone to Harvard Law School and, when a friend of mine got his degree there a few years later, he found that Charlie was a legend – with many saying he was the smartest person ever to have attended.  As a first year student Charlie was said to have regularly intimidated professors in the classroom.  While autographing my menu, Charlie said (perhaps sadly) ‘That was a long time ago … a long time ago.'”

2. “Warren Buffett once challenged Bill Gates to a game of dice. ‘Buffett suggested that each of them choose one of the dice, then discard the other two. They would bet on who would roll the higher number most often. Buffett offered to let Gates pick his die first. This suggestion instantly aroused Gates’ curiosity. He asked to examine the dice, after which he demanded that Buffett choose first.” Buffett was using a set of non-transitive dice! An explanation of these dice is here: https://www.microsoft.com/en-us/research/project/non-transitive-dice/

“From “Fortune’s Formula”, by William Poundstone 2005:

“The dean of UC Irvine’s graduate school, Ralph Gerard, happened to be a relative of legendary value investor Benjamin Graham. Gerard was then looking for a place to put his money because his current manager was closing down his partnership. Before commiting any money to Thorp, Gerard wanted his money manager to meet Thorp and size him up.  “The manager was Warren Buffett. Thorp and wife [Vivian] met Buffett and wife for a night of bridge at the Buffetts’ home in Emerald Bay, a community a little down the coast from Irvine. Thorp was impressed with Buffett’s breadth of interests. They hit it off when Buffett mentioned nontransitive dice, an interest of Thorp’s. These are a mathematical curiosity, a type of “trick” dice that confound most people’s ideas about probability.”
























Amazon Prime and other Subscription Businesses: How do you Value a Subscriber?


Businesses increasingly don’t just sell products and services in a single transaction. Subscription and other businesses that focus on recurring sales have existed for a very long time. What is new is that many more businesses have adopted a subscription approach, which makes them look a lot more like a company in the the cable television business than an auto parts manufacturer.

Successfully implementing a subscription business model can be particularly hard since the customer acquisition cost (CAC) happens up front and the revenue appears over time. These subscription businesses have a revenue profile that is more like an annuity. This revenue profile is not like the manufacturer’s business that many people learned about from a college introduction to accounting class. Unlike an annuity, the revenue stream of a subscription business is subject to risk, uncertainty and ignorance. The good news is that it is precisely because there is risk, uncertainty and ignorance that an opportunity for profit exists. The bad news is that it can be hard to capture. The reality is that if you do not capture this profit your competitors may do so.

Someone may ask: Why should I worry about this? Will it be on the test? The answer is: Yes and yes. Charlie Munger says it best: “The number one idea is to view a stock as an ownership of the business and to judge the staying quality of the business in terms of its competitive advantage. Look for more value in terms of discounted future cash-flow than you are paying for. Move only when you have an advantage.” The text in bold in the Munger statement is critical with a subscription service like Amazon Prime- you can’t understand the value of the business by looking at just one month or even a few months since it is lifetime value that matters.

Why are these new subscription businesses being created more often? The economics of a subscription business can be very favorable if you get it right. A lot of financial leverage can be generated if the customer does not need to be acquired repeatedly. Customer acquisition cost is lower for a well-run subscription business even though it is more front loaded. Yes, subscription business models can have more predictable revenues, but that is not caused by the tooth fairy. More predictable revenues are a byproduct of lower overall CAC and some operational approaches and investments in customer retention. The trade-off is that a subscription business model can also be deadly if you get it wrong. Each of the key variables in a subscription business can be either: (1) many angels working together to build something wonderful, or (2) a pack of hungry wolves that can tear the business to shreds. Propelling more businesses to adopt a subscription business  model is a simple truth: if your competitors or competitors get this model right your business may be doomed.

The benefits of this new way of doing business was chronicled well in the book The Outsiders by Thorndike. One of the major innovators of this way of doing business model was John Malone in the cable television industry. Here is John Malone talking about the model he used to build many of his businesses:

“We decided… to go on a cash flow metric very much like real estate. Levered cash flow growth became the mantra out here. A number of our eastern competitors early on were still large industrial companies — Westinghouse, GE, — and they were on an earnings metric. It became obvious to us that if you were going to be measured on earnings, it would be real tough to stay in the cable industry and grow.” “I used to say in the cable industry that if your interest rate was lower than your growth rate, your present value is infinite. That’s why the cable industry created so many rich guys. It was the combination of tax-sheltered cash-flow growth that was, in effect, growing faster than the interest rate under which you could borrow money. If you do any arithmetic at all, the present value calculation tends toward infinity under that thesis.” “It’s not about earnings, it’s about wealth creation and levered cash-flow growth. Tell them you don’t care about earnings..” “The first thing you do is make sure you have enough juice to survive and you don’t have any credit issues that are going to bite you in the near term, and that you’ve thought about how you manage your way through those issues.” “I used to go to shareholder meetings and someone would ask about earnings, and I’d say, ‘I think you’re in the wrong meeting.’ That’s the wrong metric. In fact, in the cable industry, if you start generating earnings that means you’ve stopped growing and the government is now participating in what otherwise should be your growth metric.”

The more you understand about what John Malone has accomplished in his business the more you will understand what companies like Amazon are doing in their business.

To help entrepreneurs, shareholders and lenders understand whether a given business is generating what Charlie Munger called “more value in terms of discounted future cash-flow than it is paying for” it is more than useful to calculate what is known as “unit economics.” I have written a post before about unit economics, but in this blog post I focus more on examples.

Bill Gurley sets the stage:

“[Understanding] the actual unit economics in the underlying business…requires analyzing the ‘true’ contribution margin of the business; not simply looking at gross or net revenue and the proper contra-revenue treatment, and not even looking just at gross margin as defined by the company. Many companies embed costs that are truly variable (for instance customer support, marketing, credit card processing) below the gross margin line. If you want to know if the business model truly hunts, you must pay careful attention. Otherwise, you may have simply found a company that is simply selling dollars for $0.85.”

These five factors determine the “unit economics” of a business:

  1. a customer acquisition cost (CAC);
  2. an average revenue per user (ARPU);
  3. a gross margin;
  4. a customer lifetime (which is a function of customer retention/churn); and
  5. a discount rate.

Let’s work though a key sensitivity using a fictional example. Imagine there is a business with the name “Green Oven” that delivers the food components for cooking meals along with recipes (i.e., food Legos for adults).  Assume Green Oven’s unit economics look like this:

Average revenue per user (ARPU) per month – $110

Gross margin – 33%

Monthly customer churn – 18%

Customer acquisition cost (CAC) – $450

Discount rate – 10%

The lifetime value of a Green Oven Customer would look like this:

LTV prime

That set of numbers above obviously produces an ugly lifetime value. What would happen to Green Oven’s unit economics if the rate of customer churn could be reduced to 7% a month?


Making this comparison (often called a sensitivity analysis) reveals that retention is an important factor for Green Oven. Another important sensitivity to model is the impact of a lower customer acquisition cost (CAC). Let’s take it down to $300 and assume churn is 10% in another sensitivity calculation. The numbers look like this:


It is useful to play around with a lifetime value spreadsheet and do numerous sensitivity runs to get a “feel” for how the variables interact in a given business. In this case of the Green Oven the high CAC makes high churn a potential business killer. Green Oven needs to be laser focused on reducing CAC, so it can better handle churn.

When a business reports an input into lifetime value like CAC or churn it is often an average. That may hide the fact that there are big differences in the analysis by “cohort.” A cohort is a collection of customers who share an attribute or set of attributes. For example, one type of a cohort is those customers who subscribed to a service in a given month.

Managing customer lifetime value for a business isn’t simple as David Skok writes:

“If you’re an early stage SaaS startup, still trying to get product/market fit, or experimenting with different ways to make your marketing and sales predictably repeatable and scalable, it is useful to play around with CAC and LTV to get a feel for where you are. But it’s important to note that these formulae will only yield meaningful results when your sales and marketing process and costs are predictable and scalable. Instead of spending too much time obsessing over CAC and LTV, rather focus your energies on solving the problems of improving product market fit, and making your customer acquisition, repeatable, scalable and profitable.

My apologies that there are some complex looking formulae in this article. We have provided a summary below of the key concepts, and a link to jump straight to the spreadsheet to model your own LTV. For those interested in understanding the theory behind this model, we provide our usual detailed explanation below.”

Making management of lifetime value is hard for an entrepreneur in no small part because the lifetime value variables change based on other factors like the sales channel used or geographic factors. A business can start out with very high CAC and then have it it drop over time (XM Sirius or Netflix) or have relatively low CAC and watch it rises over time (Blue Apron it appears). You can see the impact of these changes yourself by using Skok’s spreadsheet in the link to perform your own sensitivity analysis.

Why might CAC drop? There are many possible reasons including improved core product value over time, less competition, a booming economy and rising incomes, or a better sales funnel. Spending money on a growth hypothesis before a value hypothesis is a classic way to suffer horrific churn. Nothing reduces churn more than a more delighted customer.  Nothing makes it worse the an unhappy customer telling other people about their unhappiness.

  1. “If the dogs don’t want to eat the dog food, then what good is attracting a lot of dogs?” Andy Rachleff
  2. “If you make customers unhappy in the physical world, they might each tell 6 friends. If you make customers unhappy on the Internet, they can each tell 6,000 friends.” Jeff Bezos
  3. “The key is to set realistic customer expectations, and then not to just meet them, but to exceed them – preferably in unexpected and helpful ways.” Richard Branson

Why might CAC rise? There are many reasons this could happen including but not limited to greater competition, a recession, or the need to move into new market segments as the early mark segments become fully penetrated. Amy Gallo writes in a Harvard Business Review article:

“Often a high churn rate is the result of poor customer acquisition efforts. “Many firms are attracting the wrong kinds of customers. We see this in industries that promote price heavily up front. They attract deal seekers who then leave quickly when they find a better deal with another company…Before you assume you have a retention problem, consider whether you have an acquisition problem instead.” “Think about the customers you want to serve up front and focus on acquiring the right customers. The goal is to bring in and keep customers who you can provide value to and who are valuable to you.”

A cohort analysis might look like this when graphically presented (another David Skok example):


In the title of this blog post I said that I would explain how to value an Amazon Prime Subscriber. If you think about Amazon Prime as an annuity (i.e., in terms of lifetime value) it might look like this below:


This LTV calculation for Amazon Prime is based on one set of assumptions by one analyst based on incomplete information. The assumptions for Prime used by this analyst are:

ARPU: $193 a month

SAC: $312

Gross margin 29%

Churn  0.6% (customer life 167 months or ~14 years)

Discount rate 9%

You can use your own variables and David Shok’s spreadsheet (or your own) in conducting a lifetime value analysis rather than relying on Cowen. Not looking at lifetime value at all is a huge mistake. A company like Amazon is not understandable if you believe its business model is similar to the steel manufacturer you learned about in your introduction to accounting class. Trying to value Amazon’s Prime business with a P/E ratio is like trying to open a can of corn with a pickle.

An investor can pretend they do not need to do this lifetime value math, but the result will not be pleasant. Peter Lynch famously said that an investor who does not do research is like a poker player who does not look at the cards. To understand the value of the stock of a company that is using a subscription business model you need to understand the business and you can’t understand a business like Amazon without doing this lifetime value math. I will be writing more on subscription business models in subsequent blog posts.


Bill Gurley  http://abovethecrowd.com/2015/02/25/investors-beware/

David Skok: http://www.forentrepreneurs.com/ltv/

Amy Gallo: https://hbr.org/2014/10/the-value-of-keeping-the-right-customers

My blog post on the book The Outsiders: https://25iq.com/2014/05/26/a-dozen-things-ive-learned-about-great-ceos-from-the-outsiders-written-by-william-thorndike/

My previous post on Unit Economics: https://25iq.com/2016/12/31/a-half-dozen-ways-to-look-at-the-unit-economics-of-a-business/.

My previous post on CAC: https://25iq.com/2016/12/09/why-is-customer-acquisition-cost-cac-like-a-belly-button/

My previous post on churn: https://25iq.com/2017/01/27/everyone-poops-and-has-customer-churn-and-a-dozen-notes/

A few links

On churn:



On “Green Oven” comps: